TradEducation

Innumeracy

noreply@blogger.com (Williamk) — Tue, 29 May 2007 13:05:00 +0000

John Allen Paulos is his book Innumeracy writes:

Some would-be advisor puts a logo on some fancy stationery and sends out 32,000 letters to potential investors in a stock letter. The letters tell of his company's elaborate computer model, his financial expertise and inside contacts. In 16,000 of these letters he predicts the index will rise, and in the other 16,000 he predicts a decline. No matter whether the index rises or falls, a follow-up letter is sent, but only to the 16,000 people who initially received the correct "prediction." To 8,000 of them, a rise is predicted for the next week; to the other 8,000, a decline. Whatever happens now, 8,000 people will have received two correct predictions. Again, to those 8,000 people only, letters are sent concerning the index's performance the following week: 4,000 predicting a rise; 4,000 a decline. Whatever the outcome, 4,000 people have now received three straight correct predictions. This is iterated a few more times, until 500 people have received six straight correct "predictions." These 500 people are now reminded of this and told that in order to continue to receive this valuable information for the seventh week they must each contribute $500. If they all pay, that's $250,000 for our advisor. If this is done knowingly and with intent to defraud, this is an illegal con game. Yet it's considered acceptable if it's done unknowingly by earnest but ignorant publishers of stock newsletters, or by practitioners of quack medicine, or by television evangelists. There's always enough random success to justify almost anything to someone who wants to believe.

This is a great example showing how unsuspecting (& hopeful) people can be swayed into believing that a guru has magical predictive powers. It happens all the time.

Read Bestselling Book Trend Following and visit the Trend Following Blog at Michael Covel

Is Trading Style Hard-Wired?

noreply@blogger.com (Williamk) — Tue, 29 May 2007 13:03:00 +0000

Perhaps the most common assumption made by traders and trading psychologists alike is that people are capable of adapting to any market or trading methodology.

An increasing body of knowledge, however, suggests that many of the personality factors that affect decision-making under conditions of risk and uncertainty are hard-wired. Brain scans, for instance, predict who will be risk takers in gambling situations and who will be risk-averse. As one researcher bluntly puts it, "Brain activity predicts behavior."

A key element in decision-making is the brain's reactivity to loss vs. gain in decision-making. When the brain responds much more to loss than gain, individuals are far more likely to be averse to gambling. When the brain's "reward centers" respond to winning about as much as losing, the result is risk-seeking behavior. Interestingly, the brain areas that respond to winning money are the same as those that respond to cocaine or chocolate. This helps to account for the frequency of addictive behavior among gamblers--and traders.

Such individuals are not only risk-seeking, but stimulation-seeking. They have a low tolerance for boredom and use risky behavior to generate interest in their environment. Research suggests that easily bored individuals are more prone to depression and addiction than other people. Easily bored people also tend to have lower attention spans than others, increasing the odds of impulsive behavior. Such individuals would have particular difficulty adhering to trading plans and discipline.

Different brain mechanisms have been found to mediate risk-taking and risk-aversion in financial situations. A particularly interesting finding is that the dopamine reward center kicks in about two seconds prior to making a risky decision. Conversely, a brain center that is responsible for emotions of anxiety and repulsion is activated prior to suboptimal, risk-averse decisions.

We have no problem with the notion that some individuals are born with physiques that enable them to be successful in athletic contests. It is more controversial, however, to assert that some of us may be born with greater ability to make rational financial decisions than others. And there may be people with brain processes and psychological makeups who should avoid trading as assiduously as they might avoid cocaine.

It's nice to think that any trader can trade any market or methodology. The reality, however, is that we seem to be hard-wired to prefer certain levels of risk and stimulation. It may be more effective to fit trading methods to individuals than to hope to overcome hard wiring and teach a particular style to all traders.

Mechanical Trading Systems

noreply@blogger.com (Williamk) — Sun, 13 May 2007 18:12:00 +0000

Before we define a mechanical trading system it's best to understand fully the concept of a trading system:

What is a Trading System?

Trading systems are defined by a common set of rules which encapsulate all buy and sell (entry and exit) trading decisions. All trades executed following these common rules belong to the trading system.

This is easy to follow with the help of an example.

John has a share portfolio which consists of some Blue Chip shares and some smaller Speculative Shares. Even with this classification John has two distinct Trading Systems,“Blue Chip Shares” and “Speculative Shares”. Imagine the flexibility and analysis capabilities obtained by managing each trading system independent of the other!

In the example above, John could split his share portfolio into as many trading systems as he likes. Remember, you can create as many trading systems as you like, defined by an unlimited number of rules.

For example, John uses a rule that he will buy shares in all companies which have a PE ratio below 10 and volume turnover of more than $15,000,000 per day. John creates a trading system called “LowPEHighTurnover” to manage all his investments.

All future trades that John makes based upon his rules will belong to the "LowPEHighTurnover" Trading System. To extend this concept even further you can get creative and set up numerous trading systems which are independent of each another.

The benefit of creating trading systems is the high level of control and analysis capabilities which it provides. Having numerous Trading Systems is only beneficial when you have the right tools to help you with the analysis process.

What is a Mechanical Trading System?

A more advanced concept of trading systems is that of mechanical trading systems. Mechanical trading systems are designed to be totally mechanical in nature. A mechanical trading system executed correctly will exclude the undue influences of emotion, which can hinder the performance of many traders.

Human emotion is one of the most complex and hard to control areas of trading. No trader or investor has been able to conquer the market without first controlling their emotions.

Mechanical trading systems are defined by a distinct set of rules which instruct the trader what should be done and when to do it (entry timing and exit timing). It provides a signal when the trader should enter a trade and when the trader should exit a trade.

As the rules of a mechanical trading system are clearly defined, we can backtest the mechanical trading system over historical data. Backtesting is important to provide confidence that your mechanical trading system will be profitable. Backtesting is required before you undertake to commit any capital to a mechanical trading system. The results obtained from backtesting will provide an indication of the system's profitability, sustainability and highlight the characteristics of the system to illustrate how it will behave in a real life trading situation.

When performed correctly, backtesing is the closest we can get to determining the sustainability of a mechanical trading system without actually risking any money. Backtesting provides an easy way to gain confidence regarding the profitability of the system before you make the decision to commit your hard earned money to trading it.

Mechanical trading systems can be defined as a method of generating trading signals and quantifying risk independent of a trader's discretion. Although the advantages of utilising a mechanical trading system are many, most market participants agree that their greatest benefit is the tempering of destructive emotions, considered the enemy of all successful traders, from the decision making process.

Types of Mechanical Trading Systems

Mechanical trading systems which primarily use price data (high, open, low, close and volume) to derive trading signals can be classed as being either trend following or reversal based.

Trend following and reversal based trading systems have distinctly different characteristics.

Their characteristics will influence which type of trading system you decide to trade or design. The frequency and duration of trades signaled by either system are amongst the common differences between these two trading system types.

Trend following trading systems:

Trend following trading systems try to capitalise upon an established trend in the price of the security. For this reason, trend following systems tend to be traded over a longer time horizon than a reversal system.

When compared directly to a reversal system, the duration of the trades in a trend following system are distinctly longer and the number of trades taken by the system is less.

Trend following systems are most suited to be traded for long term gains as the capital and time requirement for this type of system is less than a reversal system.

Reversal systems:

Reversal systems on the other hand try to identify a change in the direction of a security and capitalise upon this change in direction.

Reversal systems anticipate a change in direction of a security and as a result will signal more trades on average than a trend following system. The increased number of trades is compensated by a shorter trade duration.

Reversal systems are most suited to traders who wish to be more active in the market. The potential for short term gains is high however reversal systems require more discipline and time to trade correctly.

Backtesting your trading system

What is going to give you the confidence to start trading your hard earned money on your trading system idea?

Any wise investor will do as much testing as possible before starting to trade a system with real money.The best option is to backtest the idea over historical data to determine how well it would have performed over that set of data.

Interpreting these results will provide you with sufficient information to assess the potential of the trading system.

When backtesting, your aim should be to replicate real life as close as possible. This means a proper backtest will need to effectively go back in time and start trading your mechanical trading system moving forward to the end of the data set.

So, how do we go about doing this?

In today's technological world, you can use the power of computers to complete the backtesting for you, to do this you will need:

1. A computer.
2. Backtesting software.
3. Historical data.

The only other alternative is to perform a manual backtest. This is not only time consuming but very hard to replicate and test variations of your mechanical system.

In other words, you should automate the backtesting process.

So long as your mechanical trading system works with just price data (open, high, low, close, volume) you will be able to utilise backtesting software to perform the test.

It will be no use backtesting, if your historical data does not enable you to test your idea. For example, you create a mechanical trading system with the following buy rule:

Purchase the share when the 10 day moving average of the close crosses above the 50 day moving average of the close.

The rule above can be tested quite comfortably over historical data which contains only price data. If, on the other hand your buy signal rule was a little more complex as detailed below:

Purchase the share when the 10 day moving average of the close crosses above the 50 day moving average of the close and the price to earnings ratio was 80% or lower than its value 4 months prior.

This rule is very complex as it introduces data which is not often supplied or maintained in a database of price information.

To successfully backtest this would involve obtaining historical data of the close as well as the price to earnings ratio (PE ratio). Obtaining historical information on a group of equities would normally consist of only the open, high, low, close and volume for each period.

Because of this limitation many mechanical trading systems are designed around purely technical indicators and rules based around only the open, high, low, close and volume information (price information).

Any mechanical trading system designed around fundamental data is really beyond the scope of retail investors due to the lack of historical data available to conduct a complete backtest.

With this in mind, remember that backtesting is not compulsory. You can start trading your own mechanical trading system without completing backtesting, it is a high risk strategy which is not advised.

Read on to learn more about the backtesting process.

With advances in technology, a wide range of trading system backtesting software is available. The benefits obtained from backtesting software cannot be underestimated. It will save you time and provide an endless opportunity to fine tune and test variations of your ideas.

A small outlay in capital to purchase good backtesting software will potentially save you thousands in the market if you have not backtested your ideas properly, it's a very wise investment if you are considering designing a mechanical trading system.

This is a quick guide to highlight some of the items which you should keep in mind when searching for backtesting software.

What backtesting methodology does it employ?

Sounds like a really complicated question, but it's not. Always remember that backtesting software should represent real life as closely as possible when it performs the test.

This way, you will have more confidence in the results. Never forget it will be your hard earned money on the line when you start trading for real!

“Real life” simply means that as we trade in our everyday lives we can make trades as much as our capital will allow.

For example, suppose you have two backtesting software applications, one of them performed the backtest by going back in time and starting from the start of the data moving forward one day at a time. The other started from today and worked its way backwards.

Which one of these represents real life the closest? Of course the first one is the obvious choice.

You should always ask the following questions about the backtesting methodology which the software employs:

1. Does the test move forward from the start of the data and step through each period of that data?
2. Does the backtest software monitor my money available for each trade and not trade if there is no money?
3. Does the software stop the test when I run out of money? In other terms does the test continue after you experienced negative equity. Remember in real life you cannot continue to trade if you have no money left.

Is the backtest software dependant upon any other software?

You need to find out if the backtesting software is dependent upon you owning another piece of software in order for it to run.

This is not necessarily a bad thing as the software may be utilising functionality from another piece of software which is superior in the industry. It is not necessarily a bad thing for the backtesting software to rely upon another piece of software, in fact, it may make the backtesting software better as the programmers and designers have had more time to concentrate on the backtesting functionality of their program with minimal time needed to be spent on the functions which the other software performs.

If you are required to own another piece of software you will be best advised to investigate that software application first.

What kind of data does it accept?

All backtesting software will require the use of data in order for it to perform its backtest.

Even when the data only consists of open, high, low, close and volume information, the software application may rely upon a certain format. Make sure the data you have or are wishing to obtain is fully compatible with the backtesting software.

Will it backtest leveraged instruments?

People will design and create mechanical trading systems for all types of instruments. The most common will be a normal share.

What if you designed a mechanical trading system for a leveraged instrument? You will need to backtest your idea using the correct leverage settings for the instrument.

If you think you will be in a position to design a trading system for leveraged instruments then you need to make sure the backtesting software caters for those instruments.

Is there a limit to the number of instruments that can be backtested?

If you design a trading system for a universe of 1,000 stocks you will need to make sure the backtesting software can cater for the large number of stocks (items) required for the backtest.

We have known some backtesting software to be limited to a maximum number of items, this is an area for concern as it puts a caveat on the backtest results and on the design of the mechanical trading system.

Make sure you can run the backtest on a limitless number of items.

Backtest results, what should I expect?

Once you have performed a backtest you will begin to analyse the results. The results you obtain from the backtesting software should be comprehensive enough to give you a clear indication of the potential of your system.

Expect nothing more than an absolute abundance of statistics and graphs to illustrate the results of your trading system.

When it comes to trading system performance data, the more the better. The more statistics and graphs you can analyse will enable you to tune and tweak you trading system enabling you to create a more powerful system which you can have confidence trading in real life.

In addition to backtesting results you will need to have the same level of detail and sophistication when you start trading your system in real life, this is where Stator - Advanced Finance Management takes over.

Remember, the more statistics the better.

Make sure the backtest recognises your account capital as it moves forward in time.

In real life you start trading with a set amount of money (capital).

If you trade this amount of capital and run out of money after one year, you can't continue. It's a simple equation, running out of money means you can't continue trading.

Make sure the backtest follows this same real life scenario, as it will be no use having ten years worth of results when your account capital reached negative figures after only one year.

In real life this event would have forced you to stop trading.

Make sure the backtest allows the use of money management.

Make sure you can play around with various money management (position sizing) models when performing the backtest.

Money management can dramatically change the results of any trading system. Having the ability to adjust your position size based upon risk is a very powerful concept which can dramatically improve the results of any trading system.

We highly recommend being able to adjust position sizing when performing a backtest.

For more information about various money management models and position sizing click here.

Understand what language the backtesting software speaks.

Computers do only what humans instruct them to do.

When you design a trading system, you want to have no limitations on the ideas which you can test. Any good backtesting software will be controlled by some programming language, make sure this language is as flexible as possible.

You will find some backtesting software uses established programming languages and others have their own programming language, either way make sure this language offers a wide range of options and flexibility.

The more flexible the programming language, the more creative your trading system can be.

Some points to bear in mind when backtesting

We previously made mention that backtesting should be designed to mimic real life as close as possible.

The following points are issues which you need to be aware of when performing any trading system backtest.

Ensure you have clean historical data.

When preparing to perform a backtest you need to ensure you have clean data. Make sure the data is correct (adjusted for splits etc) and contains the exact universe of stocks you wish to backtest.

For example, if you have designed a mechanical trading system which you wish to backtest on the Australian S&P ASX 200, your data will have to comprise of stocks which make up the S&P ASX 200 index.

Good, clean data is crucial to a proper backtest. Make sure you obtain good quality data for your backtest.

Setup is everything.

These days, running a backtest simulation will not take long at all. Be careful however that you check all the settings before you run the backtest.

It's also advisable that when the backtest is complete you re-check the settings.

If the results are too good to be true then they probably are.

You won't be the first person to backtest various trading system ideas. Many beginners fall into the trap of running a backtest and getting carried away with results which are too good to be true.

Whenever you get results which just seem too good, take the time to check and re-check your code.

Make sure you have programmed the system to represent real life and some common areas to check may be:

1 . Your entry is looking into the future. (can't do this in real life)
2 . You enter a position on the open however part of your entry criteria is the close of this same day. (can't do this in real life)
3 . You use an indicator which uses future periods to determine its value (zig zag indicator is a perfect example)

The real motto with this tip is to check and re-check your code to validate that it's representative of real life.

Searching for the Holy Grail is pointless.

Sooner or later you will find yourself testing ideas in the hope of stumbling across that magic secret which will unlock the market and all its profits.

This won't be the case, you will never create a trading system which has a 100% success rate. Many have tried and many have failed.

The Holy Grail does not exist.

You should be looking for a good trading system with minimal draw-down (the maximum equity during the trading systems life) and a good reward risk ratio.

Many trading systems have more losing trades than they do winning and the system still makes money. A perfect example are trend-trading systems made famous by the Turtle Traders, this system only had ~40% winning trades.

Successful Traders are Goal-Oriented, Disciplined, and Ambitious People

noreply@blogger.com (Williamk) — Sun, 13 May 2007 17:09:00 +0000

by Adrienne Toghraie, Trader’s Coach

“What brings you joy?" The answer should just pop out. After all, successful investors and traders are highly goal-oriented, disciplined, and ambitious people. How can you have such qualities in abundance and not know what makes you happy? Yet, strangely enough, a fair number of people cannot answer.

“Okay Adrienne" you say. “Suppose I’m one of those people who doesn’t know what brings them joy…What does that have to do with making money in the markets?" If you do not know what brings you joy, you are very likely not going to be able to sustain a long and successful career.

#The things that bring you joy can sustain you when things go badly.

When you are having a bad day, when you have experienced a serious trading loss, when you are feeling sad because a close friend has died, when your son wrecks your car, or when you begin to question what life is all about, you need to have things in your life that bring you joy. And you need to know immediately what they are so that you can call upon them to remind you that life is still good even when some things about it are going badly.

#The things that bring you joy can give you a reason to succeed.

I know a number of people who gave up successful careers in the markets because they had no reason to be successful. There was nothing in their lives that they wanted to support, to nurture, and to see to completion.

#The things that bring you joy give you the energy, enthusiasm and perseverance to keep going.

Joy is the juice in your veins, the lift in your step, and the air under your wings. It’s what keeps you working on that system and finding the answer to that nagging problem.

#The things that bring you joy combat depression and pessimism.

Negative emotional states can cause a trader to miss trading signals and lose opportunities. Pessimism can result in depression, or deepen and extend a depression. Depression can put a rapid end to a trading career.

#The things that bring you joy make you a joy to be around.

A spouse who sees you only when you are feeling joyless can begin to feel that you are a liability in life. He or she may need to fill life with the company of those who make life happy and pleasant. After all, don’t you want to be around people who are happy and can make you smile and laugh? A good and supportive marriage is one of the most important assets a trader can possibly have.

#The things that bring you joy help you to think more creatively and more clearly.

Imagination works much better when the mind is at peace than it does when it is filled with miserable and obsessive thoughts. Great ideas and insights are more likely to come in moments of joy than when the mind is in turmoil. Opportunities seem to abound when you are happy and positive. The same opportunities will be difficult to see when you are mired in pessimism. The most successful investors and traders are able to use their intuition in making decisions. Intuition is available only when your mind is at peace.

#The things that bring you joy allow you to feel more joy in the things that normally do not bring you joy.

When you are able to feel joy in one area, there is a spillover effect into other areas of your life, just as there is a spillover effect when you are feeling angry, pessimistic and upset.

Recently I worked with a client who began our session together with a long series of sad stories and laments. Clearly, Charles’ life had not been going well for a long time. His wife had left him, children avoided him and he had given up his trading career as a successful money manager. Charles was living with close friends who tried to encourage him to get on with his life and who recommended he call me.

When I talked with him, Charles sounded hopeless. I asked him what brought him joy in his life; he hesitated and barked at me, “What relevance does joy have in this conversation?" Did I not understand that there was no joy left in his life? But I was undeterred. Yes, joy was the central issue for Charles. If he had nothing that brought him joy, it was unlikely that he would have an anchor to keep him from drifting further away from a successful life. Without something that brought him joy, I would have a hard time giving him a reason to succeed. Without a font of joy, I could not squeeze out any excitement, energy or enthusiasm for the rigours of putting his life back together.

When Charles and I got together for private work I pressed him to go back to times in his life when he was doing things that made him happy. It turned out that he had loved to play the saxophone when he was at school. He had also loved to read historical novels, especially ones about submariners in World War II. In his childhood he had lived in Connecticut and had loved camping in the woods. As we progressed, he began to discover that there were many, many things that had once brought him joy that he had slowly abandoned or forgotten. I convinced Charles to spend time walking through the beautiful North Carolina forests near his home, dusting off his old saxophone and starting to play it again, and going to the library to find some of the newer historical novels and accounts from World War II.

Without any conscious thought, Charles began to find a new energy and passion for getting back into the trading game. When they saw his new sense of his own worthiness, associates who knew his ability as a money manager were eager to invest their capital with him. He is now earning money for his clients and has made positive steps to change his whole life. When I saw him several days ago, he had a bounce in his step, he was dressed like a winner, and he was filled with a sense of optimism. Charles is well on the way to recovering success and happiness. The lesson for him was that if he had allowed himself to do the things that created joy in his life, he would not have reached the bottom.

If, like Charles, you cannot say what brings you joy in life, then you too can look back to the days when you were carefree and spent time doing the things that made you happy. As you begin to list them, you will discover that the list will expand rapidly. Choose three simple things you would like to add back into your life, and then go for it. You will be amazed at the spillover effect on your work in the markets.

If you can figure out what brings you joy, then you can focus your thoughts and energy on those things in your life. The resulting positive energy will, in turn, seep into the rest of your life, including your investing and trading, and will open up new opportunities for success.

The mine field

The second set of circumstances that creates an environment for ‘heart and mastery’ comes from those who overcome tremendous adversity. Having what it takes to conquer exceptionally difficult circumstances gives you the endurance to conquer yourself and to achieve mastery.

Enter Sea Biscuit

The movie, Sea Biscuit, is a true story about how several people and one horse combined their efforts to create a champion. To make this happen they had to be in the right place at the right time, experience wonderful triumphs, face great difficulties and make unusually risky choices. All of them faced great adversity and each of them developed the ‘heart’ of a winner.

They also had the gift of being able to recognise the ‘heart’ in each other. The horse’s owner lost his son in an accident that he blamed himself for. He also lost his wife because she blamed him, too. He needed an opportunity to overcome his sadness and guilt. The trainer, who was living from hand to mouth, needed someone to recognise his special talent for connecting with animals. He was presented with an opportunity to train a horse of his choice.

As a teen, the jockey had to leave his family because they could no longer afford to support him. He longed for the opportunity to prove that he was the special person that his father wanted him to be. Of course, there was Sea Biscuit. The horse needed an environment of nurturing to show his breeding, talent and ability to be a winner. Sea Biscuit was the ultimate of what ‘heart’ can do for the soul of man. His triumph brought a nation together after the bitter days of the Great Depression by giving people hope for the future.

There are many people throughout history who have overcome great odds and adversity in their quest for greatness. Some people with ‘heart’ are:

Dr. Milton Erickson, who in spite of polio became the greatest hypnotherapist of all time.
Tiger Woods, who in spite of the race barrier became one of the greatest golfers of all time.
Lance Armstrong, who in spite of cancer in his lungs and brain won the Tour de France five times in a row Thomas Edison, who was sent home from school because the teachers said he was too stupid to learn anything, but became one of the greatest inventors in history.
Benjamin Franklin was the fifteenth of seventeen children of a poor candle maker. His first obstacle was that he had only one year of schooling. He went on to teach himself philosophy, four languages, the classics, writing for publication, science, finance, politics, diplomacy – to become one of the best educated and greatest Americans.
Annette Kellerman was a sickly and lame woman who became the World Diving Champion and was judged the world’s most perfectly formed woman.

In the ‘rags to riches’ stories that I have collected over the years, there are a few that I think about when I go through a challenging time in my own life. One that stands out is the story of a trader named Roger. He was born into a family that had a difficult time keeping food on the table and a roof over their heads. His father was in a wheelchair and took care of the three children at home. His mother, who had very little education, worked in a candy factory production line. Roger did what he could as the oldest son to help support the family by becoming a paperboy and doing other odd jobs. Since he was unable to finish high school, he thought that he was destined to do blue collar work for the rest of his days. Until the day that changed his life.

Roger was in the habit of doing good deeds for people because he saw his father and mother help others despite their difficulties. He learned from a very young age that good deeds gave you good feelings. With all of the sad moments in his life, he longed for good feelings. So he looked for opportunities to help others.

Roger was working as a maintenance man in an office building in Chicago. One day he found a briefcase filled with important and valuable items, such as contracts and certificates, in the restroom. An executive at the Chicago Board Options Exchange had hurriedly left it there. Roger returned it intact and the man wanted to reward him for his honesty. The man was impressed with Roger and asked about his life. He wanted to know how a good-looking, honourable young man was cleaning buildings for a living.

After Roger told him about his life the man offered him a job as a runner at the CBOE. Runner led to trader, trader led to super trader and super trader was able to send his brothers and sister to school and give his parents a more comfortable life.

While Roger seemed to have been given his break when he became a runner, his training for becoming a trader started from overcoming his difficult life and recognising the value of good deeds.

True grit

Yes, there is opportunity for creating ‘heart’ beyond adversity and being born into it. This third set of circumstances is for those who:

set their sights on a goal for mastery with tasks that are developed out of a good plan
seek out good models and mentors.
develop the discipline necessary to follow good rules consistently.
create a nurturing supportive environment.
become a constant student of the markets.
balance all areas of life to support mastery.
handle psychological issues that create sabotage.
work with a success coach.
become a mentor to others.

Suzy was a woman who sought out what she wanted and did whatever it took to be the best she could be. She was a high achiever in school and in the corporate world. Then she became a top multi-level marketing consultant while creating a nurturing home for her family. Suzy’s husband was looking for a new career after retirement and in the process, he and Suzy both became interested in trading. She transferred the experience of her multi-marketing skills into becoming successful as a trader. Working side by side with her husband and using the same formula for success, Suzy blossomed into becoming a master trader while her husband developed into a good trader.

The fact is that with the right formula those with the ‘heart of a trader’ will blossom while others will only be ‘good’.

Stray bullet of greatness

There is another form of greatness. There are those people who, in the process of seeking out one form of success, achieve another.

One of the most talented people that I know in the financial field has written several best selling financial books. He is an exceptional trading teacher and has developed several profitable trading systems. He is one of the best in the world at analysing markets. The only problem is that his target was to become a great trader and that success has eluded him. He has solved the problem by having someone else pull the trigger on trades for him. While he has experienced the rewards of greatness, there is a part of him that would give it all up to become a great trader.

Conclusion

I believe that the ‘Heart of a Trader’ can be developed. Yes, it is easier for some because of their experiences and resources, but even the best of traders may not reach their top performance if they do not follow a good model. The fortunate thing about working on becoming a great trader is that there is always more than one winner. Even if you only become a ‘good’ trader, in trading “Good ain’t bad."

Adrienne Toghraie, Trader’s Coach, has lectured and coached some of the most successful people around the world, and has published eight books on the psychology of trading

Back testing

noreply@blogger.com (Williamk) — Tue, 01 May 2007 07:11:00 +0000

From Traderpedia

Definition:
Testing a strategy on historical data in order to see if it would have been profitable.

[hide]

What is a backtest?

A backtest is a simulation of how a trader with a mechanical trading system would have responded to market data, i.e by buying, selling, or forgoing any transaction at all. Backtesting is a way of testing the signals given by a trading system in order to see whether it would have been profitable in the past.

As with any simulation, the more realistic the backtest, the more useful it is. Obviously, the goal of any trader is to maximize return after slippage and transaction costs (while avoiding unnecessary risk) and these costs should of course be included in the test.

The data mining problem

Just because a strategy would have worked in the past had a traderstumbled upon it does not necessarily mean it is reasonable to think it will continue to work in the future. The Super Bowl Indicator (NFC team wins, market goes up) and the hemline indicator (skirts long, sell short) are obvious examples, but don't be lulled into thinking that any strategy based on more sensible criteria is sure to work. Backtesters must be careful to avoid hyping results based on a limited set of data. There may be something special about the data the backtester used (e.g., it's all January data) that causes anomalous results. Or the results may simply have been caused by chance.

Data mining is even more of a hazard as backtesters use new programming techniques and greater computer horsepower. "Genetic algorithms" sometimes spit out eye-popping numbers when using historical data. It remains to be seen whether these algorithms actually help predict anything. As O'Shaugnessy said in What Works on Wall Street, "Torture the data enough and it will confess to anything."

How to combat the data mining problem

There are three primary ways to combat data mining.

The most obvious is to view with suspicion results that contradict common sense or other well-designed studies.

The second way to avoid data mining is to divide the available historical data into a "play" set and a "confirmation" set. Use the play set to experiment with, and then see if the confirmation set confirms your hypothesis. For example, if you had 5 years of data at your disposal to test an intra-day system, you might have a play set of 24 randomly selected months and a confirmation set of 24 different months. This method is almost sure to tell you whether you are really eliminating problem children or just trying too hard. If you do not have fairly large set of data to start with, you cannot use this technique. Be very cautious in interpreting your results.

The third way is to avoid over-optimising or "curve fitting" your system. By this I mean continually tweaking and adding parameters in ordre to increase the overall profitability. Do this to excess and you are likely to end up with a brilliant system for the period of time under scrutiny, but one that fails miserably as market conditions change. The best systems tend to be fairly simple.

Results of a backtest

Here are the questions most traders want a backtest to answer before putting money into a trading system:

Does the system provide returns that are significantly better than an appropriate benchmark?
What is the maximum drawdown of the system?
Is the system realistic in terms of slippage costs?
How many trades per year are necessary for the system?
How long is the typical position kept open in the system?
What is the ratio of the average winner to the average loser (the profit/loss ratio)?
What is the ratio of winning to losing trades (the win/loss ratio)?
What is the maximum adverse excursion?
What is the system's expected value?
What are the characteristics of the system's equity curve?
Is it realistic to assume an entry and exit could always be made when indicated?

How To Make A Million In 40 Trades

noreply@blogger.com (Williamk) — Fri, 20 Apr 2007 14:38:00 +0000

This article is a true story of how a friend of mine made a million dollars in 40 trades during a three month period. I should mention first that he did start with $100,000. I could have called this my Jerry Maguire moment. You know the movie with Tom Cruise where he decides to write a mission statement.

Think of this - double a dollar 20 time and you have over one million dollars.

$ Dollars $	Doubled
$1.00	$2.00
$2.00	$4.00
$4.00	$8.00
$8.00	$16.00
$16.00	$32.00
$32.00	$64.00
$64.00	$128.00
$128.00	$256.00
$256.00	$512.00
$512.00	$1,024.00
$1,024.00	$2,048.00
$2,048.00	$4,096.00
$4,096.00	$8,192.00
$8,192.00	$16,384.00
$16,384.00	$32,768.00
$32,768.00	$65,536.00
$65,536.00	$131,072.00
$131,072.00	$262,144.00
$262,144.00	$524,288.00
$524,288.00	$1,048,576.00

Before I start with this story I have to give you some background so that you can really appreciate the whole episode.

It all happened in the 90's. I don't even think the Euro Dollar had been introduced for trading at the time.

Anyway, it was fairly early in my trading career and a few years earlier I had taken a course on Forex trading in London. You know, one of those "I'm a guru and this is the Holy Grail courses".

I distinctly remember that the course cost me £8,500, which was a lot of money in those days, hell, its still a lot of money for a course today.

At the time, I remember coming out from the course thinking that I had cracked it. I was already planning on the car I was going to buy and what sort of massive house I was going to live in.

The course finished on a Friday and by Tuesday I was set up with a broker and ready to make my fortune.

By the following Tuesday I had blown $10,000. I couldn't believe it. I had diligently applied everything I had learned and still lost money. I was thoroughly depressed. At the time I knew very little about money management but I knew enough to know that I wasn't going to make any money trading the way I had been.

I spent the next six months reading everything I could about the Forex market. I became totally obsessed with the thing. I would sometimes work 18 hours straight, studying and testing different ideas.

During all of this I kept in touch with the guy that originally taught me the course (Lets call him Peter as he is still in business as far as I know). I realized months later that the course was useless but by this time I had got to know Peter and he was a very likeable guy, it was hard not to like him even though I knew more than he did six months after I took the course.

At the time, I lived in a beautiful village in the heart of Perthshire called Blairgowrie. Just as a side note here. If you ever go to Scotland, make a point of heading up to Perthshire. Everyone goes to Edinburgh or Glasgow but trust me, the farther North you go in Scotland the more beautiful it gets and the people are much friendlier too.

So, picture the scene. I had eventually got my act together. I was making money trading, not a lot but enough to cover my living expenses and it was in the heady days before I had children so there always seemed to be time for things.

I would get up at around 5 am, make myself a big cup of black coffee, put on some Beethoven or Enya and settle in for the morning. My favorite technique was to try to catch a move on the London opening and be finished by midday.

It's funny you know but even I can see how the action in the market has change over the years. The 5 minute charts just seemed easier to trade in those days.

This left me time for my second passion of going to the movies. Both my wife and I used to be devoted moviegoers. I mean, we would watch every single new release and even the arty foreign ones too. Nowadays, with kids, all I get to watch is Toy Story, The Lion King Or Shrek over and over again.

Back to the story. About a week before this story starts I was speaking with Peter and asked him if he knew where I could get a copy of a manuscript by WD Gann that I was after.

Anyway, about a week later Peter gives me a call and tells me that he has this guy called Fred who has just taken the course and is struggling a bit. He asks me if I would spend the day with him and just try to help him.

I knew of course that the reason he wanted me to help him was because he didn't want the guy to ask for a refund but whatever the reason was, I wasn't interested. I was in my own little groove and life was good. I was doing OK in the markets, getting to see all the movies I could watch, in short I was happy.

This is where he tempted me with something he knew I would be interested in. Somehow he had managed to get his hands on the manuscript I was after. He wanted to make a deal. He would FedEx it down to me the same day if I would spend some time with Fred. He got me with the one thing he knew I would bite at.

Arrangement were made that I would collect Fred from Edinburgh airport on Monday morning.

About two days before I was due to collect Fred, he calls me. "Hi Mark this is Fred, Peter said that we are going to meet on Monday and I just wanted to touch base with you. So how much money are you making?"

Wow, this guy was to the point. I wondered if I had made a good decision agreeing to spend the day with him.

Monday morning comes and into the arrival lounge steps Fred. Big tall guy, over six foot tall. His hair was just starting to turn grey and he was dressed in baggy jeans and a T-shirt. I placed him about 36-40 years old.

"I thought I might see some sheep running around the airport". What do you mean, I said. "You know, highlands of Scotland, William Wallace and all that stuff." We both started laughing. I knew I was going to like this guy but he had a wicked sense of humor.

We made some general chit chat on the way back to Blairgowrie and eventually we got in front of the screen where I started to explain how I trade.

Around this time I was really into Fibonacci and the approach I used at that time was the forerunner to www.surefire-forex-trading.com.

This is where the real story starts.

Fred just sat there looking at me. He had his face resting on his hand with his elbow on the table, which made his face all scrunched up like a cabbage patch doll. I went on for about half a hour. Then suddenly, Fred pretended to let his elbow fall off the table. "Oh, sorry Mark, I was falling asleep. You could stun a pig with this stuff".

"What", I said, but I knew exactly what he meant.

"Well, I'm not interested in all this crap. Just show me the good stuff, you know, the thing that makes the money."

"This is the thing that makes the money Fred."

"I'm not going to do all this mathematical stuff, there's got to be an easier way to make money than doing all this stuff. Plus, at the rate you make money, I might be 60 before I make any decent money."

I had to laugh, Fred was an entirely different animal from me. He wanted to trade and make it big but he wasn't prepared to do the work.

We spent the rest of the day talking about trading and life in general. I laughed the whole day. This guy only knew how to do things one way and that was with both barrels blazing.

Fred eventually went home and things returned to normal. A few days later I get one of many calls that were to come from Fred.

"Hi buddy, I set up my account last week and it's live today."

Great I said. "Remember to take it easy."

"Its a bit late for that me old matey, I'm short the Swiss for a million."

I just listened dumb stuck. You could and still do get incredible leverage with Forex. In those days there were no such things as mini contracts. I had just started trading with two contracts and here was Fred on his first trade, jumping right in there with ten contracts.

How big is your stop I asked him.

"Stops are for wimps buddy. When I make a couple of grand I'll close the position."

"Listen Fred, that's dangerous."

"Don't worry me old matey. You can sit up there in the Highlands and watch the grass grow while I make the real money down here."

About three hours later he calls again. "Just made $5000 bucko. Put that in your pipe and smoke it." I laughed but I was worried about him.

A few days later Fred calls again. "You wont believe this. I was going to short the Pound so I went short 30 contracts and went out for a coffee. Anyway, when I get back you will never guess what happened. I screwed up. I pressed the buy button instead of the sell button and now I'm up $15,000."

I had also been trading the Pound and there had just been a nice move but I had made about $1000.

So what are you going to do now I said. Are you going to close the position? "Hell no. Push it until it hurts me old matey".

He eventually closed the position later in the week and was up about $45,000. Over the course of the next few weeks Fred made about six trades and was increasing his leverage as he went. He was now regularly trading 30 contracts plus. After about a month and a half his account was standing at $500,000.

Quick Explanation
The pip value varies depending on which currency pair you trade but lets say that a pip is worth $10 with one contract to make this easy. Fred was trading 30 contracts or about $300 a pip. If the pair moved 100 pips that would be $30,000. Contracts in Forex are also commonly known as "lots".

Back to our story. It didn't matter how much he made he wanted to use the maximum leverage he could and push his leverage to the limit. It was madness but no amount of reason was going to stop him.

He had also had a remarkable run. I don't remember the exact number but he had very few losing trades.

I was getting more worked up about his trading than he was. I eventually couldn't take it any more and told him I was flying down to see him. I was also curious to
see how he was doing this. What mad method was he using.

As it turned out, his method was remarkably simple.

Look at this chart

Basically at around midday he would just draw a straight line across the top and bottom of any consolidation he could see on a 5 minute chart. If he had a couple of closes above the consolidation he went long. If he had a couple of closes below the consolidation he went short. There was either no stop or one so far away that it didn't matter much. He just closed the position when he felt he had made enough or judged the market to be turning on him. It was a sort of breakout technique.

Things came to a head when Fred went on holiday. He didn't particularly want to go on holiday but he had arranged this months before him started to trade.

He had arranged to take his family to Disney Land and off he went. Finally I thought, some peace and quite. But not quite.

He could only have been on the ground for a few hours when I got the call. "What's the Yen doing." Forget it I said. You need to take a break and spend some time with the family. Silence on the other end of the phone.

A few hours later he calls again. "Right me old matey, I've just bought a fax machine, fax me over a chart of the Yen." I couldn't believe what I was hearing. He wanted to trade without a dealing station and no access to charts.

"No way Fred."

"Listen up buddy, I am going to take it easy, I just want to be in the market. Send me a 5 minute of the Yen and I will keep it to ten contracts." Reluctantly I agreed but made it clear I thought he was off his head. I knew that regardless of what I said he would find a way to trade.

As it turned out, even on his two week holiday he made over $100,000. Obviously going over his 10 contract limit he promised me.

I could go on here about his trades but the incredible run finally ended one Sunday night after about three months and around 40 trades, Fred had managed to parlay his initial starting capital up to one million dollars.

Now if you trade currencies, you know that nothing much happens on a Sunday night. Asia opens but generally there are no big moves.

The phone rings about 1 am and wakes me from my sleep. "What the F%$* is happening to the Swiss." He didn't even wait for an answer, he just hung up. I lay in bed for about ten minutes thinking about what Fred had said and then curiosity got the better of me, I had to go see for myself.

I knew as soon as I saw the chart what was worrying Fred. For some reason the Swiss had gone up over 100 pips on a Sunday night. I had never seen such a big move on a Sunday and I couldn't find any news as to why this might be happening. Fred must be short the Swiss I reasoned.

I decided to call him. "Your short the Swiss right?" yes, he replied. "I just don't understand it. I thought I would place my positions ahead of Mondays opening and then this Sh*% happened. What do you think I should do?"

I didn't know. "Look, you really only have two options, close the position now or wait for the London open and see what happens. Whatever you decide put a stop in to be on the safe side."

I remember watching that 5 minute chart of the Swiss all night long and about eight am London time the Swiss began to rise again. It had moved another 80 odd pips up. I called Fred. "What did you do." Silence on the other end of the phone. "Fred, what did you do."

"I shorted it again. I thought that as it had already moved so much it must be ready for a pullback so I shorted it again. There is something else Mark but I am too embarrassed to tell you."

"What is it Fred?"

"I've been adding contracts and now its looking real shaky."

I never did find out exactly how bad his situation was that day but I could guess. Not only had he shorted the pair again he had added contracts.

After that trade, nothing seemed to go right for Fred. He had some wins but in a period of about a month he lost everything. Even his starting capital. He was the
first trader I knew who actually had a margin call. That's when the broker calls you to tell you that there is either not enough money in the account to cover the position or it is getting dangerously close to that level.

I still consider Fred a close personal friend and we have remained friends throughout all the years. It took some time but Fred to recover but he did eventual make quite a bit of money in the property game.

Here's the moral of the story. I have met some incredible traders over the years. I even know one trader who makes millions of dollars a year and before you ask, no, he doesn't share his method with me.

Of all the hundreds of traders I have met over the years I only know a handful that still trade and make money year after year. All those traders without exception have strict money management principles and a simple method or system.

Don't be in a rush to make it in trading. You need to learn this profession. You need to have money management principles in place that allows you to stay in the game even when you go through a bad patch and trust me they will come.

I asked Fred one day why he never stopped or drastically reduced the amount he was trading when he had a million dollars. This is what he said.

"I have a glandular problem, I have this huge greedy gland that just wont let me stop. When I got to a million I immediately thought, why not ten million me old matey."

Here's a scary thought. There was a time during all this when I would have believed he could have done it.

Good Trading
Mark McRae

On Randomness and Streaks

noreply@blogger.com (Williamk) — Sat, 14 Apr 2007 10:29:00 +0000

One of my favorite books is Fooled by Randomness by Nicholas Taleb

http://www.amazon.com/gp/product/158...books&v=glance

I’d suggest that you purchase it and read it cover to cover several times. The major theme of the book is that people totally fail to understand randomness – even logical, educated people. In fact, sometimes logical, educated people can be fooled even more than the non-logical, and uneducated.

For example, last week in an article by Chuck Branscomb, you learned that good traders learn to tolerate long losing streaks, including making 12 losses in a row. We got several comments on that one.

Here is one of them:

You say that a winner still knows that he's a winner even after an expected 12 losses in a row. Who in his/her right mind would "expect" 12 losses in a row?

If a system is designed to win 50% of the time, the chances are only 2 in 10,000 of getting such a result if the system is performing as expected.

Even if the system is designed to win only one out of ten (and presumably make more than enough on the one win to make up for the nine losses), the probability of 12 losses in a row is still less than 50/50 at only 28%. Getting a result like 12 losses in a row would more than likely mean that the system is not working as intended.

I understand the intent of your statement, but show me a person who "knows" that he/she is a winner with a system that loses 12 in a row, and I would like to see that system ... so that I can take the other side of the trades.

My guess is that the author of this letter is very intelligent and understands quite a bit about probability. For example, he was able to illustrate that the odds of 12 losses in a row with a 50% system are only 2 in 10,000. He’s a little off — it’s actually 0.000244.

However, his calculations were based upon making 12 losses in a row in 12 trades with a 50% system. What if you make 100 trades each year? Or what if you are a short-term trader and make 1000 trades each year? Then the chances of a long losing streak are quite large.

For example, I did 20,000 Monte Carlo simulations of 100 trades with systems that are 25% correct; one that is 50% correct, and one that is 75% correct just to see what the losing streaks might be. What I found is shown in the table below:

1.)The first column is the win percentage of the system.
2.)The second column shows the length of the losing streak that will occur100%of the time in this system. That is, you are guaranteed of having a losing streak that long.

3,)The third column shows the average losing streak for that winning percentage. You have a 50% probability of getting a losing streak this long.

4).The fourth column shows a 10% probability losing streak. Losing streaks will happen this long 10% of the time if you make 100 trades each year.

5.)The next to last column shows a 1% probability losing steak. In other words losing streaks this long will happen 1% of the time if you make 100 trades each year.
6.)And the last column shows the maximum losing streak in 20,000 simulations of 100 trades.
Losing Streaks As A Function of Winning Percentage of Your System

See Chart Attachment

Notice that with a 50% system, you are almost guaranteed to have five losses in a row in 100 trades and you’ll probably get six losses in a row. If you simply calculated the probability of getting six losses in a row, you’d say it’s unlikely because the probability is 0.0156. You’d conclude that its nearly impossible.

But it’s not impossible in 100 trades. In fact, it’s almost certain.

In our simulation, we also found that you have a 10% chance of nine losses in a row and a 1% chance of 12 losses in a row. One percent is unlikely, but not impossible. And just when you decide it’s impossible, it would probably happen for you.

I don’t have a simulator that will easily do 20,000 simulations of 1,000 trades, which is still quite likely for a short term trader to make in a year. I will easily have over 1,000 trades this year and I’m not a day trader. Many of my clients will easily have 1,000 trades each year. I’m right on about 45% of my trades and I probably have a losing streak as big as 15-20 losses in a row this year. Some of my students (who are superb traders) frequently report losing streaks as long as 20 in a row.

Most long-term trend following systems are not right 50% of the time. They are more likely to be right 30-45% of the time. Thus, the probability of having 12 losses is a row in 100 trades is no longer just a possibility – it’s a distinct probability.

So what does this all mean for you?

It simply illustrates the point that the average person does not understand randomness, even the average highly intelligent person.

Second, it says that long losing streaks are quite possible. Most people who insist on being right will typically give up their system, thinking it is no good. In reality, the system is doing what you probably should expect.

And, lastly it shows the critical importance of position sizing. If you risk 1% on each trade, then after 12 straight losses you’d probably be down about 10% (i.e., you’d be down less than 12% because you’d only be risking 1% of what’s left after each loss).

Your next trade might be a 20R winner and you’d be up — even after 20 losses in a row.

Don't worry, only 2 out of every 100 traders will pick up on this information, the other 98 will be paying for your winning trades the rest of the year

A look At Optimization

noreply@blogger.com (Williamk) — Sat, 14 Apr 2007 10:12:00 +0000

To the new systems developer one of the most exciting things to play with is optimization. Optimization is using the power of the computer to examine every possible sequence of parameters and rules to find those that have worked out best in the past. With enough computer crunching power its possible to find systems that perfectly “predicted” the past. We can run number crunching PC's on automated routines and have them analyze billions of bits of data while we are sleeping! Many traders do this long enough and eventually "discoverer" the holy grail of trading systems. They jump into the markets with their new super predictive algorithms only to find they fall apart in real trading!

“What happened?” they ask themselves. The answer is that what they created was likely a system that was a statistical coincidence (known as a "curve fit"). Curve fitting is where a system has been optimized to a unique set of historical data. The problem is that the markets will behave much differently in the future than the past, therefore, a “perfect” trading system in the past could be useless in the future. For example, your computer finds the perfect dates in the past to have bought and then sold the market. Obviously this data does not mean anything in the future. . This is a simple example but most curve fits are some complex form of this basic concept.

Lets look at another flawed example. Assume we wanted to optimize a set of nickels that were most likely to land on heads. What we could do is flip a million nickels and only select those that landed on heads. Then, we can take those remaining nickels and flip them again, once again only choosing those that land on heads. We could repeat this process over and over again each time only choosing those nickels that land on heads. At this point we might conclude that we had narrowed down our nickels to only a small handful that were “optimized” to land on heads. We could then go out and make large bets with those nickels putting all our money on heads. We would quickly make a fortune right? WRONG!

Unfortunately we would very quickly lose our money. These nickels were not optimized for heads; they always did and always will have 50/50 odds. What might have confused some is that they thought they had found a predictable set of nickels when in fact they had just found a statistical coincidence!

Because there is so much data and so much computing power available, these kinds of errors find there way into trading systems all of the time. One of the worst offenders of such flawed optimized systems can be neural networks. When developing a system its imperative that optimizing is avoided as much as possible. You need to find NON curve-fit robust systems. There can be a place for certain types of optimizing, but it must be handled correctly.

Learning to Trade: The Psychology of Expertise

noreply@blogger.com (Williamk) — Mon, 19 Mar 2007 13:16:00 +0000

by Brett N. Steenbarger, Ph.D.

When people hear that I am an active trader and a professional psychologist, they naturally want to hear about techniques for mastering emotions in trading. That is an important topic to be sure, and later in this article I will even have a few things to say about it. But there is much more to psychology and trading than “trading psychology”, and that is the ground I hope to cover here. Specifically, I would like to address a surprisingly neglected question: How does one gain expertise as a trader?

It turns out that there are two broad answers to this question, focusing upon quantitative and qualitative insights into the markets. We can dub these research expertise and pattern-recognition expertise, respectively. These perspectives are much more than academic, theoretical issues. How we view knowledge and learning in the markets will shape the strategies we employ and—quite likely—the results we will obtain. In this article, I will summarize these two positions and then offer a third, unique perspective that draws upon recent research in the psychology of learning. I believe this third perspective, based on implicit learning, has important, practical implications for our development as traders.

Developing Expertise Through Research

The research answer to our question says that we gain trading expertise by performing superior research. We collect a database of market behavior and then we research variables (or combinations of variables) that are significantly associated with future price trends. This is the way of mechanical trading systems, as in the trading strategies developed with TradeStation and the systems featured on the www.futurestruth.com site. We become expert, the mechanical system trader would argue, by building a better mousetrap: finding the system with the lowest drawdown, least risk, greatest profit, etc.

A variation of the research answer can be seen in traders who rely on data-mining strategies. The data-miner questions whether there can be a single system appropriate for all markets or for all time frames. To use a phrase popularized by Victor Niederhoffer, the market embodies “ever-changing cycles”. The combination of predictors that worked in the bull market of 2000 may be disastrous a year later. The data-miner, therefore, engages in continuous research: modeling and remodeling the markets to capture the changing cycles. Tools for data mining can be found at www.kdnuggets.com.

There are hybrid strategies of research, in which an array of prefabricated mechanical systems are defined and then applied, data-mining style, to individual stocks to see which ones have predictive value at present. This is the approach of “scanning” software, such as Nirvana Systems’ OmniTrader. By scanning a universe of stocks and indices across an array of systems, it is possible to determine which systems are working best for particular trading vehicles.

As most traders are aware, the risk of research-based strategies is that of overfitting. If you define enough parameters and time periods, eventually you’ll find a combination that predicts the past very well—by complete chance. It is not at all unusual to find an optimized research strategy that performs poorly going forward. Reputable researchers develop and test their systems on independent data sets, so as to demonstrate the reliability of their findings.

Can quantitative, research-based strategies capture market expertise? I believe the answer is an unequivocal “Yes!” A perusal of the most successful hedge funds reveals a predominance of “quant shops”. Several research-based stock selection strategies, such as Jon Markman’s seasonal patterns (www.moneycentral.com) and the Value Line system (www.valueline.com), exhibit long-term track records that defy mere chance occurrence.

And yet it is also true that many successful traders neither rely upon mechanical systems nor data-mining. Indeed, one of Jack Schwager’s most interesting findings in his Market Wizards interviews was that the expert traders employed a wide range of strategies. Some were highly quantitative; others relied solely upon discretionary judgment. Several of the most legendary market participants—Warren Buffet and Peter Lynch, for example—employed research in their work, but ultimately based their decisions upon their personal synthesis of this research. Quantitative strategies can capture market expertise, but it would appear that all market expertise cannot be reduced to numbers.

Developing Expertise Through Pattern Recognition

The second major answer to the question of trading expertise is that of pattern recognition. The markets display patterns that repeat over time, across various time-scales. Traders gain expertise by acquiring information about these patterns and then learning to recognize the patterns for themselves. An analogy would be a medical student learning to diagnose a disease, such as pneumonia. Each disease is defined by a discrete set of signs and symptoms. By running appropriate tests and making proper observations of the patient, the medical student can gather the information needed to recognize pneumonia. Becoming an expert doctor requires seeing many patients and gaining practice in putting the pieces of information together rapidly and accurately.

The clearest example of gaining trading expertise through pattern recognition is the large literature on technical analysis. Most technical analysis books are like the books carried by medical students. They attempt to group market “signs” and “symptoms” into identifiable patterns that help the trader “diagnose” the market. Some of the patterns may be chart patterns; others may be based upon the identification of cycles, configurations of oscillators, etc. Like the doctor, the technical analyst cultivates expertise by seeing many markets and learning to identify the patterns in real time.

Note how the pattern recognition and research answers to the question of expertise lead to very different approaches to the training of traders. In the research perspective, traders learn to improve their trading by conducting better research. This means learning to use more sophisticated tools, gather more data, uncover better predictors, etc. From a pattern recognition vantage point, however, trading success will not come from performing more research. Rather, direct instruction from experts and massed practice leads to the development of competence (again like medical school, where the dictum is “See one, do one, teach one”).

Another way of stating this is that the research viewpoint treats trading as a science. We gain knowledge by uncovering new observations and patterns. The pattern recognition perspective treats trading as a performance activity. We gain proficiency through mentoring and constant practice. This is the way of the athlete, the musician, and the craftsperson.

Can expertise be acquired by learning patterns from others and then gaining experience identifying them on one’s own? It would seem so: this is traditionally how chess champions and Olympic athletes develop. There are also examples of such expertise development in trading: Linda Raschke’s chatroom (www.mrci.com/lbr) is an excellent example of a learning device that takes the pattern recognition approach. Users of the site can “listen in” as Linda—a Market Wizard trader herself—identifies market patterns in real time. My conversations with traders who have enrolled in this service leave me with little doubt that they have acquired profitable skills, eventually moving on to becoming successful independent traders. Richard Dennis’ experiment with the “Turtles” is perhaps the most famous example of how expertise (in this case, a pattern-based trading system) can be successfully modeled for people with little market background.

And yet there are nagging doubts about the actual value of the patterns typically described in market books and tapes. A comprehensive investigation of technical analysis strategies by Bauer and Dahlquist found very little evidence for their effectiveness. An attempt to quantify technical analysis patterns by Andrew Lo at MIT found that they did, indeed, contain information about future market moves, but hardly as much as isportrayed in the popular literature. Because pattern recognition entails a healthy measure of judgment, it is very difficult to demonstrate its efficacy outside of the expert’s hands. In other words, the expert trader may be utilizing more information in trading than he or she can verbalize. This is certainly the case for chess experts and athletes. While they can describe what they are doing, it is clear that their proficiency extends well beyond the application of a limited set of rules or patterns.

This phenomenon has been the subject of extensive study in psychotherapy research. It turns out that there really is a difference in results between expert therapists and novices. But it also turns out that there is a difference between what expert therapists say they do and what they actually do in their sessions. This was noted as far back as the days of Freud. While he advocated a set of strict therapeutic procedures to be followed, Freud’s own published cases deviated from these significantly. What appears to work in therapy is not what the therapists focus on—their behavioral techniques, psychoanalytic methods, etc.—but the ways in which these are employed. Using techniques in a sensitive way that gains the client’s trust and fits with the client’s understandings is more important than the procedures specific to those techniques.

So it may be with trading. Expert traders describe their work in terms of price-volatility patterns, momentum divergences, or a nesting of cycles, but it might be the ways in which these patterns are employed thatmakes for the expertise. Great traders may be able to identify patterns in their work, but it is not clear that their greatness lies in these patterns.

Implicit Learning: A New Perspective

The term implicit learning began with the research of Brooklyn College’s Arthur Reber in the mid 1960s. Since that time, it has been an active area of investigation, producing numerous journal articles and books.

Implicit learning can be contrasted with the research and pattern recognition perspectives described above, in that the latter are examples of explicit learning. By conducting research or by receiving instruction inmarket patterns, we are learning in a conscious, intentional fashion. The implicit learning research suggests that much of the expertise we acquire is the result of processes that are neither conscious norintentional.

A simple example drawn from Reber’s work will illustrate the idea. Suppose I invent an artificial “grammar”. In this grammar, there are rules that determine which letters can follow given letters and which cannot. If Iuse a very simple grammar such as MQTXG, then every time I show a subject the letter M, it should be followed by a Q; every time I flash a T, it should be followed by an X, etc.

The key in the research is that subjects are not told the rules behind the grammar in advance. They are simply shown a letter string (QT, for example) and asked whether it is “grammatical” or not. If they get theanswer wrong, they are given the correct answer and then shown another string. This continues for many trials, generally in the thousands.

Interestingly, the subjects eventually become quite proficient at distinguishing the grammatical strings from the ungrammatical ones. If they are shown a TX, they know this is right, but that TG is not. Nevertheless,if you ask the subjects to describe how they know the string is grammatical or not, they cannot verbalize any set of cogent rules. Indeed, many subjects insist that the letter arrangements are random—even asthey sort out the grammatical ones from the ungrammatical ones with great skill.

Reber referred to this as implicit learning, because it appeared that the subjects had truly learned something about the patterns presented to them, but that this learning was not conscious and self-directed. Reberand subsequent researchers in the field, such as Axel Cleeremans in Brussels, suggest that many performance skills, such as riding a bicycle and learning a language, are acquired in just this way. In such cases,we learn complex competencies, but cannot fully verbalize what we know or reduce our knowledge to a set of patterns or principles.

Such implicit learning has been demonstrated in the laboratory across a variety of tasks. Cleeremans and McClelland, for example, flashed lights on a computer screen for subjects, with the lights appearing at sixdifferent places on the screen. The subjects had to press a keyboard button corresponding to the location of the light on the screen. There were complex rules determining where the light would flash, but theserules were not known by the subjects. After thousands of trials, the subjects became very good at anticipating the location of the light, as demonstrated by reduced response times. Significantly, when the lightswere flashed on the screen in a random pattern, no such reduction in response time was observed. This was a meaningful finding, since the patterns picked up by the subjects were not only outside their onsciousawareness—they were also mathematically complex and beyond the subjectsomputational abilities! (Like the markets, the patterns were actually “noisy”—a mixture of patterns and random events.)

It appears that much repetition is needed before implicit learning can occur. The thousands of trials in the Cleeremans and McClelland study are not unusual for this research. Moreover, it appears that the state ofthe subjects’ attention is crucial to the results. In a research review, Cleeremans, Destrebeckqz, and Boyer report that, when subjects perform the learning tasks with divided attention, the implicit learning suffersgreatly. (Interestingly, conscious efforts to abstract the rules from the stream of trials also interfere with learning). This has led Cleeremans to speculate that implicit learning is akin to the learning demonstrated byneural networks, in which complex patterns can be abstracted from material through the presentation of numerous examples.

The implicit learning research suggests a provocative hypothesis: Perhaps expertise in trading is akin to expertise in psychotherapy. While therapists say their work is grounded in research and makes use oftheory-based techniques, the actual factors that account for positive results are implicit, and acquired over the course of years of working with patients. Similarly, traders may attribute their results to the research orpatterns they are trading. In reality, however, the research and patterns serve as rationales that legitimize the absorption of markets over a period of years. It is the implicit learning of markets across thousands of“trials” that makes for expertise, not necessarily the conscious strategies that traders profess.

Implications for Developing Expertise in the Markets

Such an implicit learning perspective helps to make sense of Schwager’s findings. There are many ways of becoming immersed in the markets: through research, observation of charts, tape reading, etc. Thespecific activity is less important than the immersion. We become experts in trading in the same way that subjects learned Reber’s artificial grammars. We see enough examples under sufficient conditions of attention and concentration that we become able to intuit the underlying patterns. In an important sense, we learn to feel our market knowledge before we become able to verbalize it. While simply “going with yourfeelings” is generally a recipe for trading disaster, I believe it is also the case that our emotions and “gut” feelings can be important sources of market information.

The reason for this is tied up in the neurobiology of the brain. In his excellent text The Executive Brain: Frontal Lobes and the Civilized Mind, New York University’s Elkhonon Goldberg summarizes evidence thatsuggests a division of labor for the hemispheres of our brains. Our right, nonverbal hemispheres become activated when we encounter novel stimuli and information. Our left, verbal hemispheres are more active inprocessing routine knowledge and situations. When we first encounter new situations, as in the markets, we tend to process the information non-verbally—which means implicitly. Only when we have made thesepatterns highly familiar will there be a transfer to left hemisphere processing and an ability to capture, in words, some of the complexity of one’s understandings. As we know from studies of regional cerebral bloodflow, the right hemisphere is also activated under emotional conditions. It is not surprising that our awareness of novel patterns, whether in artificial grammars or in markets, would appear as felt tendencies rather
than as verbalized rules.

o finally we get to the traditional domain of the trading psychologist! How do we know when our feelings convey real information for trading and when they merely provide interference from our conflicts oversuccess/failure, risk/safety, etc.? Developing trading expertise is not so simple as following such slogans as “tune out your emotions when you are trading”. Much of what you might know about the markets maytake the form of implicit knowledge that is encoded nonverbally and experienced viscerally.

This is an area that I am currently researching, and I welcome readers to stay in touch with me about the results. I will make sure updated information is posted in a timely way to my personal page atwww.greatspeculations.com. I also hope to have my own book out on the topic early in 2003; my page will also keep readers abreast of that development. But in the remainder of this article, allow me to engage in afew speculations of my own regarding the implications of implicit learning for trading success.

Many are called, few are chosen – I believe the implicit learning perspective helps to explain why so few traders ultimately succeed at their craft. Quite simply, they cannot outlast their learning curves. If,indeed, it takes thousands of trials to generate successful implicit learning, a great number of traders would have been bankrupted by then. Many others might not survive that number of trials simply due to the timeand energy required. It is impossible to hold a full-time job and generate the degree of immersion in the markets needed for implicit learning. On the other hand, it is impossible to obtain a full-time income fromtrading without developing the mastery conferred by years of experience. Part-time traders never develop expertise for the same reason that part-time chess players or athletes are unlikely to succeed. For purelypractical reasons associated with raising a family, making a living, etc., few people can undergo the “starving artist” phase of skill-building.
Emotions interfere with trading – This is a near-universal observation among full-time traders and captures an important understanding. Fear, greed, overconfidence, self-blame—all of these can undercut eventhe most mechanical trading. Indeed, when Linda Raschke and I surveyed 64 traders for their personality and coping patterns, the factor of neuroticism—the tendency to experience negative emotions—emerged asa major factor associated with trading difficulties. This makes sense from an implicit learning perspective. To the degree that a trader is focused on his or her fears, self-esteem, fantasies, etc., attention is drawnaway from the learning process. The problem may not be emotionalism per se; there are many highly emotional, but successful traders. Rather, the issue may be the degree to which emotions interfere with one’scognitive processing by competing for attention. Focusing on negative emotions may be a much larger problem than actually experiencing them. Many outstanding traders “explode” when they make a rookie error.For them, however, the storm blows over quickly; less successful traders appear to be less able to let the issue go. As a result, they become caught in a cycle of blame, increasing self-consciousness, and furtherblame. As a psychologist, my leaning is to help traders experience their frustration and get over it quickly, rather than “overcome” it altogether. (In my chatroom session with Linda Raschke, I will be addressing how
to accomplish this).
The advantages of learning trading vs. investing – If the internalization of complex patterns requires many thousands of observations across different market conditions, the challenge for the trader is makingthis process as efficient as possible. My sense is that there may be an advantage to learning trading, as opposed to investing, simply because short-term traders are apt to observe many patterns in the course of asingle day or week. The investor, conversely, may note a pattern every few months or years, greatly extending the amount of time needed for implicit learning. This dynamic would help to explain why many of themost successful traders I have met have had experience working on the exchange floors. In the fast-paced environment of the floors, a trade may last seconds to minutes, with many trades placed per day. Complexresearch strategies and chart analyses fly out the window when time frames are compressed to that degree. Instead, traders become so immersed in the markets that they acquire the (implicit) ability to read
moment-to-moment patterns of momentum and price change. This creates an ideal implicit learning environment; having so many patterns to read per day makes the development of expertise much more efficient.Ironically, it also might help account for difficulties floor traders often experience when they attempt to trade off the floor. Without the contextual cues that help them process those price and momentum shifts, floortraders lose their edge—even though they may think they are employing their same, successful trading methods.
Developing technologies for training traders – If we look at how experts are trained in other fields, we notice a common factor: an intensive period of apprenticeship in which the student works under a masterand obtains continuous instruction and practice. Consider, for example, the cultivation of expertise in the martial arts. Many years will be spent in the dojo studying under a sensei before the black belt is conferred.Instruction alternates with practice; rehearsal of techniques alternates with the application of techniques in real-life (tournament) conditions. The online medium has created a variety of promising strategies fortraining traders, such as Linda’s chatroom, real-time market commentary via weblog, and services that allow simulated online trading. My sense is that we will see an accelerated shift from services that emphasizetrading techniques to comprehensive trading “dojos” that incorporate real-time instruction, practice, and coaching. Already we are seeing expert instruction modules built into conventional software programs such as
Metastock. This move toward implicit learning environments strikes me as a most promising application for peer-to-peer networks, as traders share research resources and trading experiences and learn from eachother. (See www.limewire.org for more information on Gnutella and P2P networking).
Developing technologies for facilitating learning – This is my primary research interest in trading psychology. A broad array of research suggests that learning is mediated through the brain’s prefrontalcortex, which also controls attention, concentration, planning, and other executive functions. We also know that children with learning disabilities are significantly more likely than others to possess neurologicaldeficits associated with the frontal lobes, including attention deficit hyperactivity disorder (ADHD). Elkhonon Goldberg cites considerable research that indicates we can improve the functioning of our frontal cortexthrough structured exercises, much as we can build our muscles in the gym. Such exercises have been used, for example, in delaying the onset and progression of Alzheimer’s disease. Is it possible, however, todevelop super-states of concentration and learning in a mental gym the way that bodybuilders can hone their physiques in a weight room? I believe we can. I am currently working with Dr. Jeffrey Carmen onbiofeedback strategies that directly measure regional cerebral blood flow to the prefrontal cortex. Utilizing infrared sensors to detect heat changes in the forehead (reflecting increased frontal blood flow), it ispossible for traders to know exactly how much of their mental processing power is available to them at all times. Moreover, it is possible for them to learn strategies for increasing their frontal activation andmaximizing their optimal learning states. This would allow traders to process each trading day (or lesson) as thoroughly as possible, creating more efficient learning.
My research to date suggests that the state of mind induced by the biofeedback exercises is not unlike the state that people enter during hypnotic induction or meditation. It is a state of relaxed and focusedconcentration. Such a mind frame minimizes the impact of emotional interference at the same time that it quiets the verbal, internal dialogue that permeates much of our cognitive lives. Following Goldberg’shypothesis, I believe that the capacity to enter such states of consciousness may allow us to efficiently process novel information by facilitating right hemispheric activation, even as it dampens emotional arousaland the interference of critical, verbal thinking. This very much fits with psychologist Mihalyi Csikszentmihalyi’s observations of “flow” states among highly creative and successful individuals. The learning ofexpertise may depend as much upon the mind state of the learner as the quality of the instructional materials.

Conclusion

I began this article with a straightforward question: How does one gain expertise as a trader? We have seen that expertise is often described as the outcome of an explicit research process or as an explicitacquisition of knowledge about recurrent patterns. Much skill-based learning, however, is acquired implicitly, as the result of processing thousands of examples. Small children learn language, for example, longbefore they can verbalize rules of grammar and syntax; we learn complex motor skills, such as hitting a baseball, without ever being able to capture our expertise in a way that could be duplicated by another person.

While immersion in research and in pattern recognition can indeed produce trading expertise—a finding made clear by Schwager—the key ingredient in trading development may be the immersion, not the researchor the patterns per se. If this is true, efforts to find the best trading system or the most promising chart pattern are off the mark. The what of learning trading may be less important than the how. If you want to become a proficient trader, the most promising strategy is to immerse yourself in the markets under the tutelage of a master trader. You need to process example after example under real trading conditions, withfull concentration, to develop your own “neural network”.

I believe the most exciting frontier for trading psychology is the development of tools and techniques for maximizing implicit learning processes. Such techniques would assist in the acquisition and utilization ofexpertise by training individuals to sustain states of consciousness in which they are open to implicit processing. As I hope to demonstrate more thoroughly in my forthcoming book, there are reasons forbelieving that experienced traders possess greater expertise than they are aware of. This tacit knowledge, to use Michael Polanyi’s memorable term, reveals itself during “hot streaks” in trading and thosewonderful experiences where we just “know” what the market is doing and place winning trades accordingly. Too many traders look to emulate others. The secret to success, conversely, might well be to gaingreater access to the expertise we have already acquired implicitly and learn to become the traders we already are when we’re at our best.

Well, if you’ve followed me thus far through a lengthy article you no doubt have much of capacity for attention and concentration needed to become a master trader! In the coming months, I hope to elaborate manyof the ideas and techniques alluded to in this article, and I encourage you to stay in touch regarding new directions and developments.

With that, I will part with a last research finding from Reber. Remember those artificial grammars that people had to learn, such as MQTXG? Letters were displayed to subjects that either followed the grammar (i.e.,Q could only follow M; T could only follow Q, etc.) or that did not. The subjects did not know the rules of the grammar, but over many trials could figure out which combinations of letters were right and which werewrong. Suppose, however, that the grammar is changed in the middle of the experiment, so that the new constructions follow the rules of NRSYF instead of MQTXG. Will subjects continue to display implicit learning?

The answer is enlightening. After many trials with the initial grammar, without knowing the rules, subjects will choose “MQ”, “TX”, and “QT as grammatical constructions while rejecting “QM”, “XT”, and “TQ”. Oncethe grammar is switched, the subjects’ learning goes out the window and their guesses retreat to chance levels. But with enough new trials, subjects pick up the new grammar and are able to recognize “NR”, “SY”,and “RS” as grammatical and reject “RN”, “YS”, and “SR”. In other words, people not only learn complex patterns implicitly; they continue their implicit learning when the patterns shift. This has major implicationsfor the development of market expertise. The markets are always changing, but as long as we stay in our optimal learning modes, we can adapt with them.

Brett N. Steenbarger, Ph.D. is Associate Professor of Psychiatry and Behavioral Sciences at SUNY Upstate Medical University. Dr. Steenbarger is an active trader and author of The Psychology of Trading (Wiley, 2002). He writes feature columns for the MSN Money website (www.moneycentral.com) and several trading publications, including Stocks Futures and Options Magazine (www.sfomag.com). These articles and a daily trading weblog are linked at www.Greatspeculations.com.

Expose Yourself! A Powerful Technique for Breaking Emotional Patterns in Trading

noreply@blogger.com (Williamk) — Sun, 11 Mar 2007 13:14:00 +0000

Written by Brett N. Steenbarger, Ph.D

Traders love patterns. We trade chart patterns, oscillator patterns, historical patterns, cyclical patterns—you name the pattern, chances are there’s someone trading it. Much of trading boils down to patternrecognition and the ability to quickly identify and act upon profitable patterns as they occur. This is particularly challenging for active futures and options traders, who must read the patterns, make their decisions,and place their orders within a matter of seconds. Processing market patterns in the midst of our own emotional patterns—our tendencies toward impulsivity, hesitation, frustration, and regret—is one of the greatest challenges of active trading.

It is always sobering for traders to realize that they are every bit as patterned as the markets they’re trading—and sometimes far more so. In this article, I will draw upon two decades of experience as a clinical psychologist to illustrate a powerful technique for interrupting and changing repetitive emotional and behavioral patterns that disrupt trading. The technique is a cognitive-behavioral method known as exposure, and—in the Ranger tradition described by Brace Barber, Linda Rashcke, and me in September’s issue—it is a powerful tool for challenging oneself for exemplary performance.

Becoming Your Own Therapist

Extensive studies by Axel Cleeremans and Arthur Reber suggest that, with sufficient experience, people can learn to read patterns in data and anticipate future data sequences. Interestingly, this pattern recognition is intuitive and implicit rather than verbalized: we know things long before we know we know them. Such findings contradict the common belief that successful trading requires an elimination of emotions. Our feelings, like market data, consist of relatively weak—but vitally important—signals in the midst of considerable noise. Our sensitivity to market patterns often remains hidden amidst the pushes and pulls associated with trading fears and ambitions. Traders can learn to become their own therapists by using techniques such as exposure methods, not to dull or eradicate emotion, but to gain control of their cognitive worlds and better extract signal from noise.

The problem, you see, is not simply our patterns of anxiety, guilt, anger, or discouragement. The problem is that we cannot control these patterns. No one consciously plans to fail to pull the trigger on a promisingtrade; nor does anyone want to impulsively leap into a non-trending but volatile market before evidence of a breakout is at hand. As I emphasize in The Psychology of Trading (Wiley; January, 2003), such emotionaland behavioral patterns play themselves out against the will of the trader, in spite of our best-laid trading strategies and sophisticated market research.

For most of us, the scenario is embarrassingly familiar: We make plans to get into shape, to diet, or to treat others better—and what happens? All too easily, we lapse into our ruts. At the time we make ourresolutions we are sincere. But under the influence of old patterns, the resolutions lose their force. The plans that we had carefully crafted fall by the wayside, like so many good dieting intentions.

Why?

Our trading (or dieting or exercise) plans are anchored to a particular state of mind—associated with a particular set of thoughts, feelings, and physical sensations. When something intervenes to shift us to anotherstate, we lose our anchoring. We no longer have vivid and immediate access to the motivating experiences that spurred our initial intentions. The key is not to spend months and years psychoanalyzing why we are“self-defeating” or otherwise lack “self-esteem”. Rather, we need to become our own therapists and learn to remain anchored, even in the face of market and emotional forces that could disrupt our trading plans.That is the purpose of exposure-based techniques.

Overcoming Problem Patterns Through Exposure

Let’s take a classic example of how exposure can break seemingly intractable emotional patterns. Ellen is suffering from a condition known as panic disorder. Sudden, episodes of anxiety hit at seemingly randommoments, greatly interfering with normal activities. These episodes are so scary that she is afraid she is losing control and might even die. As a result, Ellen develops a fear of her panic episodes—somethingknown as “secondary anxiety”. Sure enough, her fear of the panic attacks leads her to become increasingly anxious and actually triggers further attacks. By the time Ellen makes it to therapy, she has been caughtin a continuous cycle of worry, anxiety, and panic.

If I were using exposure methods with Ellen, I would first teach her a skill, such as a deep-breathing, progressive muscle relaxation method. This involves learning how to slow oneself down by reducing the rate of respiration and deepening the breathing while eliminating physical tension by gradually tensing and relaxing muscle groups from one end of the body to the other.

Figure One Relaxation Training: A Useful Behavioral Technique

Step One: Deep Breathing – Close your eyes and begin breathing deeply, slowly, and rhythmically. Your breathing should be from the diaphragm, and should not be forced or exaggerated in any way. During the deep breathing, you keep your body as still as possible, performing the exercise in a quiet, distraction-free environment.

Step Two: Mental Focus – Fix your attention on a peaceful, relaxing stimulus while you are performing the deep breathing. You can play instrumental music through headphones if this is helpful and/or focus your attention on soothing mental images or scenes. For instance, you could imagine yourself in vivid detail walking along an ocean beach, smelling the salt spray, feeling the warmth of the sun, hearing the crashing waves, etc. The key is to make the music and/or imagery all absorbing, tuning out internal chatter.

Step Three: Muscle Relaxation – Once you are feeling more relaxed, begin at one end of your body (such as your toes) and tense and relax one musclegroup at a time, working your way to the other end of your body. Tenrepetitions for each muscle group, with hearty tensing and slow, easy relaxing,works well. This can be performed while you are breathing slowly and deeply tothe accompaniment of the music and/or imagery. >From toes and instep tocalves, knees, thighs, buttocks, back, shoulders, arms, wrists, fingers, neck,and forehead, you progressively undo your body’s tension.

Step Four: Self-Awareness – When you have finished the muscle relaxation,slowly open your eyes and notice how you are feeling. By now you have beenbreathing deeply and slowly, with an altered focus and physical relaxation, forquite a few minutes. Very often there are particular physical sensations thataccompany your relaxed, focused mode that traders call the zone. I find that Iexperience a quiet feeling in my head, as if I am somewhat removed from theworld. Such sensations can become your cue, alerting you that you haveentered the zone and are ready to deprogram old patterns via exposure.

Note – At first it can take a while to get to the zone. With practice, you canbecome very good at the breathing and muscle relaxation and enter the zonein a matter of minutes or even seconds. The key is frequent rehearsal, firstunder normal conditions, then under conditions of gradually increasing stress.

Once Ellen has learned this method, the exposure can begin. I would ask her to take a few rapid and shallow breaths, simulating hyperventilation. This exposes Ellen to the some of the same physical sensations that she experiences during the early phases of her panic attacks. It also summons those panicky thoughts and feelings that have become deeply associated with the physical sensations of anxiety. When Ellen begins to re-experience a bit of her anxiety, I instruct her to perform the deep breathing and muscle relaxation. She continues with the relaxation work until the initial anxiety sensations are eliminated.

After Ellen learns to extinguish the anxiety that comes from a few rapid, shallow breaths and then from more prolonged hyperventilation, I then have her perform more intensive exposure exercises. I may have her spin around in the room, recreating the feeling of dizziness that comes with her panic attacks. Later, I might encourage her to provoke panicky sensations by entering situations (such as a crowded shopping mall) that are associated with anxiety. In each case, she would expose herself to the very problem pattern that she has been trying to avoid, but would always limit the exposure and immediately follow it with the rehearsal of a coping skill. With daily practice between sessions, severe problems such as panic disorder can be successfully treated within a matter of weeks.

What makes this technique work?

Most of our problem patterns are painful; no one likes feeling anxious or depressed. It is only human nature to want to avoid emotional pain. In avoiding our problems, however, we never learn the control necessaryfor their elimination. By gradually and progressively exposing ourselves to stressful circumstances—all the while practicing ways of coping and maintaining control—we build a sense of mastery. This is how peoplelearn to overcome crippling phobias and debilitating traumas. No amount of talk substitutes for the first hand experience of directly facing fears time and time again and staying in control. Repeated successchanges the self-image, and it alters our self-talk. Suddenly, we really begin to feel and believe, “I can do this!”

Applying Exposure Methods to Trading

If you are going to serve as your own therapist in the exposure-based mode, the cardinal rule is: You always must activate a problem pattern in order to overcome it. It isn’t enough to think about your problems ortalk about them. You must actually experience your problem patterns in real time, gradually and progressively, and make conscious efforts to counteract those patterns. If your trading problem is triggered byincreasing your size, you will need to gradually and steadily trade larger. If your impulsive trading pattern occurs during trendless, low volatility markets or in the opening minutes of trading, that is when you willneed to work on yourself.

Fortunately, we can speed emotional change through a process known as imaginal exposure . Imaginal exposure can be thought of as the psychological equivalent of paper trading. Instead of starting out withreal-time problem situations (known as in vivo exposure), we can vividly imagine scenarios associated with our negative patterns—triggering some of the feelings of greed, fear, doubt, and regret—and mentallyrehearse strategies for dealing with those scenarios. Imaginal exposure is not as powerful as facing problems in vivo (much as paper trading lacks the immediacy of actual trading), but it is a useful starting point inbuilding the sense of success and mastery. Just as athletes have found mental rehearsal to aid Olympic performance, the mental tackling of trading challenges can prepare us for the real thing.

Let’s consider an example:

Lou is an active futures trader, with a little over a year of experience under his belt. He has made most of beginner’s mistakes and has learned from them, carefully planning his trades, limiting his losses, andscaling in and out of positions with initial sizes that are adjusted for market volatility. He largely trades the ES and NQ eminis in a short-term breakout mode, attempting to catch 1-4 swings per day depending upontrend and volatility conditions. His entries are based on dual RSI oscillator readings, using short-term (intraday) and longer-term (swing) parameters. While he has been generally successful, he notices that he hasperformed relatively poorly on upside and downside trend days. He finds that he hesitates too long in entering the market and then is too quick to exit the trades once they are profitable. As a result, he takes smallbites out of the moves that should be providing him with much of his profit.

An examination of problematic trend days reveals that these begin with a gap at the open in which price moves sharply up or down relative to the last trade of the previous day. This gap immediately triggers negativethinking on Lou’s part, much of which reflects feelings about having missed the apparent high or low in the market. During this period of regret, he is not actively following price action or planning an entry. Instead,he finds himself hoping for a pullback so that he might have a better entry point (and a reprieve from his self-recriminations). Price, of course, does not accommodate to his desire and moves even further from theopen, now registering an “overbought” or “oversold” signal on the short-term oscillator. Lou uses this as further justification to hold off on entering a position, allowing him to miss a good segment of the morningtrend.

This problem seems unusually rookie-like for an experienced trader, so we examine Lou’s overall trading performance. Sure enough, we find that his worst losses have occurred when opening gaps in the markethave been reversed. These false breakouts have left him buying at the early highs and selling at the lows, starting his day with solid losses and shaking his confidence. This allows us to see that what appears to bethe problem—the failure to enter the market early during trend days—is actually a coping mechanism designed to minimize the possibility of losses. Unfortunately, it also minimizes opportunities!

Our exposure therapy for Lou begins with skill teaching, as in the case of Ellen. We teach Lou a method for behavioral self-control that involves slow, rhythmic deep breathing and soothing imagery and encouragehim to practice this until he becomes skilled at maintaining his composure. In addition, however, we also want Lou to learn some vital trading coping skills. He needs a set of rules for distinguishing potential trenddays from those that may reverse and/or rules for quickly identifying reversals once they occur. For example, his own research and a little mentoring from experienced traders might teach him that gaps that occuron X-period breakout highs or lows in the NYSE TICK are more likely to show continuation than gaps that occur without such breakouts. Alternately, he may find that moves from opening gaps that remain intact byY o’clock are more likely to continue through the day than those that partially fill.

Once Lou has identified his trading rules for the problem situation and learned a method for cultivating self-control, the exposure work is ready to begin. First we can start with imaginal exposure, encouraging Lou toenter his relaxed mode with slow, diaphragmatic breathing and eyes closed. In this mode, he vividly imagines an preopening news report that sends the market gapping lower, well outside its prior Globex range. Hemaintains the visualization of the scenario as he practices his slow breathing and mentally rehearses the appropriate trading strategies. Thus, for instance, he might image the TICK plunging to a multi-day low onthe opening move and the SP failing to fill its gap on the first TICK bounce toward zero. This would be his trigger for a short entry, and he would clearly visualize each step he would take in monitoring the market,placing his order, setting his stops, etc. A similar set of visualizations could also facilitate the rehearsal of exit strategies.

Once all discomfort is extinguished in the mental rehearsals, the next step in exposure work would be applying the skills in paper trading. Using historical market data, we would have Lou advance charts bar by barin trading simulations of trend days while rehearsing his self-control and trading strategies. Only when these simulations proceed successfully (i.e., eliminating anxiety) would Lou undertake real-time, in-vivoexposure, beginning with small positions and building to larger ones. (The speed with which Lou progresses from imaginal exposure to paper trading to in vivo work would depend upon the severity of the problemsand the intensity with which he rehearses the techniques. Research suggests that fewer but longer, more intensive exposure sessions are more effective in eliminating negative emotional patterns than a greaternumber of brief exposures.)

The idea is that, before Lou confronts another potential trending day in the market again, he will have experienced multiple successes in handling such days in imagination and then on paper. It is therepeated experience of mastery and success that provides the power behind exposure-based intervention. Nothing so builds confidence as repeatedly facing and overcoming one’s fears. (See Figure 2 for keys tosuccess in the exposure method).

Figure Two Keys to Success With Exposure Methods

Patience – Taking the time to become fully relaxed before starting the exposure is crucial. Give yourself enough time to reach the zone (see Figure
One).

Persistence – A key to extinguishing negative patterns is repetition. Applying coping skills to problem scenarios again and again, in imagery and in vivo
makes stressful situations safe and familiar.

Gradualism – Set yourself up for success by starting with manageable versions of your problem patterns and imaginal exposure before tackling your
greatest challenges in vivo.

Consistency – These are short-term techniques, but applying them intensively and consistently on a daily basis provides superior results.

Realism – Exposure can break old problem patterns, but by itself won’t instill new patterns of success. Nothing substitutes for experience and research in
the markets!

A Final Note

There are many psychological approaches that can enable us to gain control of our problem patterns. Exposure-based methods are particularly useful for futures and options traders because they can beself-administered and often produce rapid results. Such methods cannot overcome all problem patterns; sometimes people with chronic difficulties need additional forms of treatment, including medication.Nevertheless, when emotional reactions are situational rather than chronic—and especially when you can isolate the trading situations that trigger the problem patterns—exposure-based techniques are excellent
mechanisms for gaining control and staying anchored to trading plans.

Notice, however, that I have emphasized the need for proper, researched trading strategies to accompany the exposure methods. As an experienced clinical psychologist and trader, I can assure you that self-helptechniques alone will never enable you to master the markets. If you want to know how to trade a candidate trend day, an intraday range breakout, or an afternoon consolidation of a morning trend, you damned well better have researched those market conditions and generated some rules and techniques to guide your entries and exits. Otherwise, you will be teaching yourself to focus and relax while you lose your hard-earned capital.

What psychological methods can do is provide you with the self-control to implement your well-researched trading strategies. That is important. Consistency of effort, not the home run trades we all like to talk about, best positions us for trading success.

Being Overwhelmed and System Development Part 3

noreply@blogger.com (Williamk) — Fri, 09 Mar 2007 12:53:00 +0000

My research suggests that the problems people have in developing a trading system fall into five different categories.

The first three areas prevent traders from ever starting (or finishing) the development of a trading system. These include computer/technology phobia, procrastination, and being overwhelmed by the whole process. The last two problems tend to prevent the trader from coming up with a workable system. These include: perfectionism and judgmental biases in your thinking.

In an earlier article we covered procrastination. This week let’s take a closer look at the feeling of being overwhelmed.

Being Overwhelmed

The most difficult thing to overcome, at least when you are in the middle of it, is being overwhelmed by any particular task. And when it comes to developing your own trading system, I see traders get overwhelmed again and again. In this case, your energy is probably low and your head is just swimming with details. Moreover, you don’t understand all of the concepts you need to and you don’t know what to do next. Here’s an example,

John was in the process of developing a trading system. He’d read about ten books on systems and indicators that are used in futures and stock trading. All the indicators confused him and when he thought about varying the parameters of each indicator his mind started spinning. He’d also attended several seminars in which various systems were recommended and taught, but he was not sure they were for him. He was feeling even more confused. The costs were mounting up and taking a toll on his trading capital and that added more pressure. He’d just bought a computer system with all the software to make developing a system easy. But there were so many details to learn. There were at least three manuals to read for him to operate the computer system and they didn’t even tell him where to begin his own development work. The details just kept piling up. John was feeling more and more stressed and soon all he found himself doing was going over everything he had to do without seeming to accomplish anything. He felt desperate to get something done soon or he’d run out of money!

John’s problem is typical of what happens when people are overwhelmed. However, the problem can be solved when you realize there are basically three aspects to being overwhelmed: 1) the concentration on details as opposed to the big picture; 2) being out of balance in your life in some way so there is undue pressure on you; and 3) the lack of a plan to get out of the mess.

The average person has a processing capacity of seven, plus or minus two, chunks of information. When people start concentrating on details, then their capacity is quickly exceeded. When your focus on the details becomes uncomfortable, because of pressure from some source, the feeling of being overwhelmed really starts to set into the mind.

Most people can easily handle a lot of details. In fact, you do so all of the time. However, if your life is out of balance and conflict is created because your needs are not being met, then the details take on a different meaning. Small details that were once trivial seem very important. The pressure to sort out the details multiplies because you create more details as a result of your imbalance. Soon it all builds into a vicious cycle of being overwhelmed! Yet it all started from the pressure of life being out of balance in some area. Maybe just one area is throwing your life out of balance? Is it your finances? Your relationships? A family crisis? A health problem? Balance your life and you’ll be amazed how overwhelming problems suddenly disappear.

Lastly, when people are overwhelmed it is because they don’t see the big picture and thus lack a plan to get away from the details. Probably the sense of being overwhelmed just came over you. You didn’t realize how much your financial pressure (or whatever the pressure) was taking a toll on your ability to think. You also didn’t realize how much you were getting bogged down by the details of system development. Because you don’t have an overall plan, you don’t know how to deal with the details.

Getting Out of Being Overwhelmed.

If you are in the process of developing a trading system and are currently feeling overwhelmed, then the first thing to do is take a break from the task that is giving you the feeling. Take a day off, or perhaps even a week, and just relax. Go to a beach or a lake and just relax looking at the water.

The next step is to determine what aspect of your life is giving you so much pressure. Where is it coming from? (Finances? Relationships? Health? etc.)

Find out what part of you (aspect of your personality) is responsible for the pressure. Once you know which part, you can negotiate with it. Find out how to meet its needs and if it will agree to let you continue with the task of developing a trading system. For example, you may have (1) to agree to give so much time each day to meeting the needs of that part (2) to set a deadline for the development of your trading system and/or (3) to agree to devote full attention to that part once the deadline occurs. Perhaps you have a part of your personality that finds the system development “no fun.” We can call that your “fun” part. To negotiate with your fun part you could agree that once you meet an objective or a deadline then the fun part can have it’s chance to do whatever it is that you think of as fun. [Parts work is covered extensively in the Peak Performance Home Study Course.]

Lastly, you must develop an overall plan for developing your trading system. Work out your objectives in detail! Once your objectives have been written down, you can then develop a plan for meeting those objectives. Divide the plan into various tasks and set a deadline for meeting each of those tasks.

About Van Tharp: Trading coach, and author Dr. Van K Tharp, is widely recognized for his best-selling book Trade Your Way to Financial Fre-edom and his outstanding Peak Performance Home Study program - a highly regarded classic that is suitable for all levels of traders and investors. You can learn more about Van Tharp at www.iitm.com.

Perfectionism and System Development Part 2

noreply@blogger.com (Williamk) — Tue, 06 Mar 2007 21:31:00 +0000

My research suggests that the problems people have in developing a trading system fall into five different categories.

The first three areas prevent traders from ever starting (or finishing) the development of a trading system. These include computer/technology phobia, procrastination, and being overwhelmed by the whole process. The last two problems tend to prevent the trader from coming up with a workable system: perfectionism and judgmental biases in your thinking.

In earlier articles we’ve covered procrastination and the feeling of being overwhelmed. This week let’s look at perfectionism.

PERFECTIONISM

Perfectionism, in contrast to what some might expect, has an extremely negative impact on performance. People often strive to be perfect in what they do because their parents demanded they be perfect as children. Unfortunately, these lofty standards sometimes keep them from ever coming close to achieving them. Perfectionists waste time with unnecessary tasks. Businessmen make less effective decisions, traders make less money, and athletes perform poorly—all because of the high standards they set for themselves.

But the vicious problem perfectionists have is not just created by lofty standards. You can have lofty standards without being a perfectionist. Instead, perfectionism means those standards are tied into your self-esteem. If you don’t achieve those standards (and for most perfectionists, those standards are all‑or‑none), then you feel like less of a person. The perfectionist has trouble tolerating a mistake or handling a distraction. Perfectionists tend to have all‑or‑none thinking; so everyday little setbacks lead them into a world of despair.

Here is how the perfectionist mind- set can create lowered performance—the opposite of the desired result. The likelihood of a person achieving any outcome depends on two primary beliefs: 1) the belief that the behavior attempted will produce the outcome and 2) a belief that you are capable of producing the necessary behavior. The perfectionist has extremely high standards, by definition, which suggests their outcome may not be directly obtainable as a result of the behavior. More importantly, the perfectionist tends to be his or her own worst critic when these high standards are not achieved. At first, the perfectionist’s criticism drives him forward towards his goals. But as he repeatedly fails to achieve them, the self‑criticism gets much stronger and the person begins to create a wall around himself making the task impossible. As a result, the desired result of nearly impossible standards frequently creates below‑average performance.

Let’s take a look at Elmer:

Elmer was a perfectionist who was trying to develop a trading system that would win in nine out of ten trades and would make five times as much money as he was risking on any given trade. When he first tried to develop the system, it was just profitable after commissions and slippage. But when he saw the results—only a 2% gain each year—he wanted to beat his head into the wall. “How could you be so stupid to think that an approach like that would work?” he wailed. After three failed attempts, he was beside himself. His family found him hard to live with—he was uncivil and didn’t spend any time with them. He just locked himself in his computer room doing more testing and feeling more and more unsatisfied with himself. Normally, Elmer would have just given up after about six months. But in trading, he was exceptionally committed to find something that would meet his standards. He’d abandon a lot of good ideas before testing them because of his self‑criticism. Those he did test, no matter how well they turned out, would not meet his criteria for acceptance. Eventually, Elmer’s wife left him and Elmer found himself broke, without a family, or even a trading system that met his standards.

Poor performance among perfectionists is well documented in many fields. Psychologist David Burns, for example, found that perfectionist insurance agents, those who linked their achievement to their self‑worth, earned on the average $15,000 a year less than their non-perfectionistic counterparts.

Similarly, highly successful athletes tend to show a lack of perfectionist tendencies. For example, elite male gymnasts who qualified for Olympic competition tended to give much less importance to past poor performance than did a group of highly talented gymnasts who failed to qualify. The latter group, in fact, would rouse themselves into near panic states by dwelling on the images of past failure and turning those failures into excessive self-doubt and thoughts of impending tragedy. Think about it—the best baseball hitter in any given year will only get a hit about 3.5 times out of ten. If that player dwelled on the 6.5 times he didn’t get a hit, his chances of getting exceptional performance would be slim.

Perfectionists tend to find themselves under a great deal of emotional stress. They drive themselves hard, while at the same time, being their own worst critic. For example, when a perfectionist falls short of a goal, he or she is probably screaming criticisms at themselves for not meeting his/her own lofty standards.

Joe was a trader on a diet. One day he ate a tablespoon of ice cream and scolded himself by saying, “I shouldn’t have done that. I’m a pig.” His self-critique so upset him that he went on to eat the entire quart of ice cream. And, of course, by the time the quart was finished, he’d berated himself so much that the whole idea of a diet seemed hopeless.

How does this cycle of lofty standards tie into a person’s self esteem development? One theory holds that perfectionism develops when a child is regularly rewarded with love and approval for outstanding performance, but severely criticized for substandard performance. The child, in order to gain parental acceptance, begins to take on the parent’s high standards. And, in order to avoid criticism from the parents, the child begins to criticize him/herself. Soon the young child begins to anticipate mistakes that will lead to a loss of acceptance and starts criticizing himself for the slightest mistake. The logic is, “If I criticize myself, I’ll do better and then my parents will love me more”. But, of course, self‑criticism leads to feeling bad and then even poorer performance. And suddenly, the vicious cycle of high standards leading to poor performance, common to almost all people with this trait, ensues. A perfectionist has started down the road to ruin.

Getting out of the perfectionist trap. The best solution to getting out of perfectionism is probably to seek professional help to get rid of the perfectionist decisions that you made some time in the past. However, there is a five-step program you can do on your own to help you make progress.

First, make a list of the advantages and disadvantages of being perfectionist with respect to your trading (or in anything for that matter). Once you have the list, notice how the advantages may not be as great as the disadvantages. This should give you some insights about your standards and what you are doing to yourself.

Second, since your perfectionism comes from all‑or‑none standards, spend a day investigating how well the world can be evaluated by such all‑or‑none standards. For example, notice what happens when you decide that food must either be terrific or awful. What happens when you decide that a room is either totally clean or totally messy? What happens when you decide that a person is either beautiful or ugly? Intelligent or stupid? Or fat or thin? And, of course, as you are doing this notice how distorted all-or-none thinking is and then think about your perfectionist standards.

Third, keep a daily written record of self-critical statements you make. You might notice how irrational some of these thoughts are, even though they may seem quite plausible when you think them. Give yourself a reward for being able to write down at least 50 such thoughts in a day. Your reward, of course, is for your self‑awareness—not the negative thoughts. At the end of the day, examine what you’ve written down and notice the distortions in the thinking.

Fourth, for several days keep a record of the activities you do. Before you undertake each activity, estimate how satisfying you think the activity will be. When you finish the activity, record how satisfying you felt it actually was and how effectively you performed. What will happen is that you will notice your personal satisfaction is not necessarily correlated with superior performance. When you learn to move toward what gives you satisfaction, rather than superior performance, you will be on the road toward making your life work. And quite often-superior performance will follow.

Lastly, each day while you are developing a trading system, set behavioral standards that are about 10% of what you would normally expect of yourself. When you accomplish those new standards, agree to be proud of your performance and congratulate yourself. If you achieve more than that, fine! But always celebrate when you achieve your new standards. If necessary, get help from someone close who is not a perfectionist in setting your standards. Most people, when doing this exercise, find that the lower they set their standards, the higher their productivity suddenly becomes.

Procastination and System Development Part 1

noreply@blogger.com (Williamk) — Sun, 04 Mar 2007 08:21:00 +0000

My research suggests that the problems people have in developing a trading system fall into five different categories.

This week I’d like to focus on procrastination which is big hindrance for so many system developers.

So many of us have a hard time getting started—especially when it comes to the task of developing a workable trading system. Yet postponing the task creates even more problems.

What is behind procrastination problems of this sort? Often, a major cause is the fear of failure, especially since the result of completing the task is an opportunity to play a risky game like trading. For example, if you’ve tried trading without a plan, you know how risky it is and part of you may be so afraid of the consequences of trading that you are having difficulty starting to develop the plan. Or, perhaps you’ve quit your job to start trading full time, but you’re so afraid of the results of not trading well that you cannot complete the job of developing your system.

If you’re uncertain of your ability to perform, either based on past experience or a general lack of self-confidence, you’ll probably find it difficult to begin. And the greater your time pressure to perform, the more fear you will create.

Sometimes the fear of success will produce the same result—continually postponing the development of a trading system. People fear success because it will bring something new. Suppose you become “rich” and, based on your experience, you don’t like all the implications of what it means to be “rich.” Perhaps your friends will no longer want to be associated with you or perhaps they’ll try to take advantage of you when you have more than they do. Or perhaps you think wealthy people are stingy and narrow-minded. You think "I don’t want to become stingy."

Another reason you might procrastinate about developing a trading system is lack of interest in that portion of the task. You don’t like the idea of playing around with computers, testing numbers, and doing all of the work. Maybe it reminds you too much of school. Lack of interest, like a fast growing weed sending out roots in all directions, can strangle motivation and make it impossible to even start a simple task. All you wanted to do is get about the business of trading. As a result, you just trade, but you have never tested what you are trading. You just prefer to make mistakes the hard way.

Perhaps the work involved in developing a trading system reminds you of someone you do not like. Someone you dislike told you to do it and you feel resentment—or perhaps someone you dislike always used to do things like develop trading systems. You don’t want to be like that person, even though you know you have to do the work, so you tend to put it off.

The more you dislike the idea of developing a trading system, or even doing certain parts of the task, the more you will tend to push it away. This means you’ll leave the toughest part of the job for that portion of the day when your energy is lowest or you are likely to make a lot of mistakes.

Lastly, the most important part of developing a trading system is to develop the objectives for the system. Once you have the objectives down, then the task of developing a system really is fairly simple. Getting your objectives down is 50% of the task. Until you have your objectives written down, you have no way of knowing what you want or of knowing when you’ve got it. How can you even monitor your progress, a major factor in ongoing procrastination, until you know exactly what you want? In contrast, once you know what you want, you can set deadlines for each phase of the project.

How to overcome procrastination.

First, you must realize that procrastination comes from you and take control of the situation. Make a commitment to get the job done. Also concentrate your focus on starting the project (or the next phase) rather than finishing it.

Next, write down all of your objectives for your trading system. At this point, you should know what you want, the tasks involved in producing it, and standards you will have for knowing when each part of the task is complete. When you know what has to be done next, it’s much easier to concentrate on doing it.

Third, divide the task of developing a trading system into steps. Rank the steps in terms of priority and then in terms of your desire to do them. Set deadlines for completing each step and announce those deadlines to the world. If you find that one portion of the job is particularly onerous, then break it into subtasks and give yourself a deadline for each subtask.

Lastly, begin the next step. Concentrate on taking each step and then begin.

Remember that Lao Tse, the great Taoist teacher, once said, “A journey of a 1000 miles begins with a single footstep”

Do you Think Like a Trader?

noreply@blogger.com (Williamk) — Sun, 04 Mar 2007 08:19:00 +0000

Take 1 – The Idiot

A penniless bum walks in to a bar and sees a sign on the wall and jumps for joy. Before the bartender can ask him what he wants he says ‘I’ll see you tomorrow’ and leaves.

Take 2 – The Norm

A man walks in to a bar and sees a sign on the wall and smiles. The bartender asks him what he wants. The man says ‘A pint of beer please’. The bartender gives him his beer, the man drinks it, pays, and leaves.

Take 3 – The Trader

A trader walks into the same bar, sees the sign, and gets a sly grin on his face. The bartender asks him what he wants. He says ’How much is beer?’ The bartender says $5 a pint.

The trader says ‘No, not how much I have to pay, how much do you pay for beer?’

‘Why should I tell you that?’ says the bartender.

‘I’ll make it worth your while’ says the trader.

‘OK’ says the bartender ‘I pay $2.50 a pint, now what do you want?’

‘I want to sell you some beer at $2 a pint’ says the trader.

‘How much beer?’ the bartender asks.

‘As much as you can take’ says the trader.

‘Where is it?’ says the bartender.

‘Oh, I don’t actually have any beer, I just want to agree to sell you some’.

‘You’re drunk or insane’ says the bartender ‘Get out of my bar’.

The trader leaves in disgust muttering something about the misleading sign.

Question: What did the sign say?

Contact Us if you can’t work out the answer.

Paul King
PMKing Trading LLC
www.pmkingtrading.com

Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part Three.

noreply@blogger.com (Williamk) — Mon, 26 Feb 2007 08:12:00 +0000

So far in this series, we have looked at biases regarding randomness, which is the tendency people have to seek patterns where none exist and to invent the existence of unjustified causal relationships. Because people attempt to understand and make order out of the market, they assume that the longer a trend continues, the more likely it will suddenly turn around. This manifests into the "gamblers fallacy," which is a very common trap that traders fall in to and lose money when they do. And, last week we examined data reliability as it relates to the degree to which information reflects what is really happening. We focused on the representation bias, availability bias, anchoring bias, and hindsight bias.

Today we continue with four common misuses of sampling variability in relation to system development, and finish with some tips to help overcome all of these biases.

Sampling Variability. Most people misuse the basic concepts of sampling theory in making predictions and designing trading systems. The first principle, which is highly abused, is that you can make more accurate estimates of the true population probability from larger samples than from smaller samples. In other words, you can get a much more accurate estimate of the reliability of a trading signal from a large sample than from a small sample. In our earlier example, Jack said that his pattern predicted a higher market price 35% of the time. The accuracy of his estimate would be much better if it were based on 100 measures of the pattern than if it were based on 20 measures. Unfortunately, most people follow a bias called the law of small numbers. Once they observe a phenomenon occurring a few times, they believe they understand it and know its likelihood.

People tend to form their opinions based on a few cases, and fail to revise their opinions upon the receipt of new data to the extent that they should, based on probability theory. Traders tend to stick to their old opinions rather than updating them as new information becomes available.
We call this the conservatism bias. This points out the importance of doing a thorough, objective testing of your market observations on a set of data that is different from the data in which you made the observation.

Traders want consistent information from various sources, such as three oscillators based upon the same data (which of course are likely to show similar results). However, this consistent information will lead to increased confidence, but not to increased accuracy of prediction.
We call this the consistency of information bias. What it means is that traders are likely to add more indicators in order to get more consistent information so they can feel confident about it. But adding more indicators is not likely to give one more accurate information. This points out the importance of developing a simple, robust trading system.

A fourth major misuse of sampling variability is that people fail to understand that the amount of variability in a sample is positively related to the degree of randomness in the sample. Once you have observed a relationship in a set of data, it is no longer random with respect to that relationship. The more relationships you observe with respect to various parameters in the data, the less random the data is with respect to those parameters. Unfortunately, system developers frequently make this mistake when they use a sample of data to optimize a system and then test the system on the same data. Once a set of data has been used to optimize a system’s parameters, then it is not random with respect to those parameters. As a result, when you use the same sample of data to test the system, you can expect it to do well in the test, but this has nothing to do with how it will work as a system trading real money. Data must be tested on a sample that is independent from the sample used to observe the original relationship.

How to overcome judgmental biases

You probably cannot totally overcome the effect of the various judgmental biases. One reason is that one of the most prevalent biases is the ego bias in which people decide, “Yes, I understand all of this, but it applies to other people, not to me. I’m a very special person and it doesn’t apply in my case.” Nevertheless, if you are willing to assume you are human and that these biases do apply to you, then you can take steps to minimize their impact.

Remember, your job as a trader is to find an edge in the markets. You must capitalize on that edge, so you will make money in the long run, while doing everything possible to preserve your capital in the short run. As a result, I strongly recommend that you spend a lot of time writing down your objectives and designing something to meet those objectives.

What is an objective?

Your objective is your goal, your target. It is the thing that you want to attain or accomplish.
Objectives set the roadmap for the entire system development process. How would one know how to get someplace if they didn’t know where they were going first? It is easy enough to see that if one trader had an objective such as “I want a system that trades long-term stocks, that requires my attention only once each week and makes 20% per year” compared to a trader’s objective that was “I want to actively trade my mother’s retirement account for four hours each day, without holding overnight positions” then two completely different systems would be required. The objectives or goals are very different. There are endless configurations of objectives. The point is you need to specifically know what it is that you are trying to attain; and only then can you develop a trading system that will help you attain it.

Observe the markets as an artist would. Be creative. Determine relationships in the market that occur over a wide variety of markets and market conditions. Remember, you are not trying to explain the markets, but just determine some market relationships you can capitalize upon. The more widespread the relationship—does it occur in different markets and different types of markets—the more likely you will be able to profit from it.

Be willing to be unique. Think about how you can best represent the price of the market. Notice relationships in the patterns of price movement that you can capitalize upon. Once you have observed some relationships, figure out how to measure them. If you can avoid common indicators, then you probably have a real edge.

Simple is probably better. Why? Because the more complex the relationship, the more likely it is to be unique to particular markets and the less likely it is to make you money.
Be sure you understand the edge the relationships you observe in your data give you. Do your observations make sense? How do they give you an edge? Also be sure that you can write down your observations in enough detail so you can recognize them as they occur and not just in hindsight.

Understand money management so you can capitalize on your observations. Trade according to a predetermined plan rather than your emotions.

Be sure to objectively test your observations on extensive market data that is different from the data you used to observe the relationships in the first place. Objective testing is very important because with subjective testing you will tend to see what you want to see. In other words, the market will confirm your expectations.

Many of the psychological issues described in this article are covered in my How to Develop a Winning Trading System that Fits You workshop and home study program. These programs will help you clarify your objectives, and then show you how to design a trading system to meet those objectives.

About Van Tharp: Trading coach, and author Dr. Van K. Tharp, is widely recognized for his best-selling book Trade Your Way to Financial Fre-edom and his outstanding Peak Performance Home Study program - a highly regarded classic that is suitable for all levels of traders and investors. You can learn more about Van Tharp at www.iitm.com.

Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part Two.

noreply@blogger.com (Williamk) — Sun, 25 Feb 2007 21:24:00 +0000

Last week we looked at the randomness bias, which is the tendency people have to seek patterns where none exist and to invent the existence of unjustified causal relationships. Because people attempt to understand and make order out of the market, they assume that the longer a trend continues, the more likely it will suddenly turn around. This manifests into the "gambler's fallacy" which is a very common trap that traders fall in to and lose money when they do.

This week we will cover the topic of data reliability and biases that come up in this area.

Reliability. When people obtain information, they fail to assess how reliable their data is, where reliability refers to the degree to which information reflects what is really happening. What traders observe in the market, with the possible exception of floor traders and other market makers, is not the market, but some sort of visual representation of the market. Thus, you are responding to a bar chart or a candlestick chart, or a point and figure chart, or to a representation of the market profile, etc.—and not to the real market. Furthermore, few people make decisions from that information alone. Instead, they distort the information even more by using indicators. These indicators are essentially shortcuts or heuristics that people have thought up to condense, organize and make sense of the data. Interestingly, there are hundreds of possible indicators—in fact, hundreds of thousands if you count various permutations and combinations—but most traders use only about 20 of the most common ones in their decision making.

Market information is certainly distorted, and thus less reliable, when it is transformed into various indicators. The less reliable the information is, the less value it has for predicting. Using our example from last week when Jack observed patterns in the market, reliability is a measure of how accurately Jack’s pattern actually predicts a sharp move in the market. Many people might notice a pattern or relationship in the market and then use it in developing a system without ever determining how reliable the relationship is. Accurately knowing how well the pattern predicts the move is very important information for any person wanting to develop a trading system.

A lot of the biases people have in their decision making tend to distort reliability in some way. For example, we have many biases keeping us from knowing the true probability of an event happening. The true probability refers to the actual probability of the event occurring as opposed to a statistical estimate of the probability from a small sample.

One such bias that keeps people from developing a good trading system is called the representation bias. We tend to imagine that what we see or expect to see is typical of what can and/or will occur. Thus, if you observe a pattern in the market, you expect it to occur. If you develop some concept about the market, you will look for data to support that concept in the market, and you will probably find it whether it exists or not.

Once again, if you do not test objectively, and understand the results of the testing, you will probably find that your observations, in developing a trading system, tend to confirm what you expect to find. Thus, the representation bias is particularly important when it comes to assessing various trading signals. Are you considering the true probability rate in assessing your indicator? That is, are you considering the percentage of time a particular indicator is followed by the predicted outcome? Probably not!

I cannot overemphasize enough that trading indicators are merely ways of representing things of interest. Does a significant chart pattern actually mean that buyers are about to dominant sellers, or vice versa, and produce a significant price change? Of course not! It merely represents the possibility such an event might occur. Thus, any indicators you develop for buying or selling in markets are your way of representing potential trading opportunities. It is not the opportunity per se. Yet most traders, because of this particular bias, act as if the indicators are what they represent. It is like the indicators (be they stochastic, RSI, or moving averages) start becoming reality, instead of a representation of a concept or a belief in your head. When you realize this, you will become much more attuned to what trading is all about and less concerned about indicators and understanding the market.

Another bias that keeps people from understanding the true probability of an event happening, and thus distorts its reliability, is called the availability bias. We make predictions based upon how available the information is to us instead of the true probability rate in the population. Thus, when you first start looking at the market, the data sample you use will determine what you observe. In addition, strong emotional experiences, which affect how strongly information stands out in our minds, tend to strongly bias our decisions.

When people start to develop an estimate of how much a trading system can earn in a year or how many winning trades it will have, or any other estimate of its reliability, they tend to start with a set point. They then make adjustments to that figure according to anticipated changes in conditions. The initial set point is called an anchor. The dangers associated with using anchors in our decision making about trading systems (or anything else) is called the anchoring bias.

The first danger is that you assume there is some relationship between the anchor and what you are predicting. For example, in order to predict the price of the market a year from now, you would probably start making your estimate with the anchor of today’s price. Over a short period of time it may be an accurate basis for beginning to make an estimate (i.e., today’s price is a good starting price for forecasting the price in two or three days), but over a longer period of time the strategy does not allow for the unpredicted or the unexpected. That is why one of the most important parts of developing a trading system is extensive planning. And this extensive planning should include a careful consideration of everything that might go wrong.

The second danger in the anchoring bias is that people make an assumption that the initial set point or anchor itself is meaningful. For example, if you use the results of your testing to predict future results, you are assuming that those results are meaningful and will not change dramatically over time. This is probably true if your testing data is different from the data you used to develop the system and included enough samples to make future estimates reliable. But those are big “ifs.”

Another bias that tends to have a significant effect on trading decision-making is hindsight bias. People tend to see relationships in the market after they occur, and then assume they knew it all along. It’s very easy to point out such a relationship after it occurs. I’ve worked with a number of clients who claim that they cannot follow their signals. However, what tends to happen is that they do not recognize the signals while they occur. Instead, they see many possibilities in the data. But once the signal is complete, it is too late! They then criticize themselves for not taking it when it occurred. The typical response is, “I knew it all along. Why didn’t I take that signal?”

This problem will not occur if you write down your criteria for a signal in enough detail so that it could be entered into a computer. You can then make a checklist for your signal (or computerize it). Once you do, you will always see a signal when it occurs or the computer will see it for you. Thus, you really will know whether or not you actually knew it all along.

About Van Tharp: Trading coach, and author Dr. Van K. Tharp, is widely recognized for his best-selling book Trade Your Way to Financial Fre-edom and his outstanding Peak Performance Home Study program - a highly regarded classic that is suitable for all levels of traders and investors. You can learn more about Van Tharp at www.iitm.com.

Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part One.

noreply@blogger.com (Williamk) — Sun, 25 Feb 2007 19:37:00 +0000

At any given instant, over two billion bits of information impinge upon your senses. Yet consciously, we can only process “7 +or - 2 chunks” of information. This tremendous reduction in information necessary to act upon external signals or make decisions is accomplished through various “heuristic” rules or shortcuts.

These rules, which are essential if you are to make any decisions at all, are both a strength and a limitation. They offer strength in that they provide tremendous shortcuts to making decisions. Decision-making would be practically impossible without them. However, they are a major weakness because people are unaware they are even occurring or how much they distort and delete information and bias our decision-making. For example, two such biases that make it difficult for most people even to make money in the markets are the gambler’s fallacy and the tendency to be risky in the realm of losses and conservative in the realm of profits—the opposite of what it takes to become a successful trader.

In this three-part article, we’ll explore several of these biases and how they might affect one’s trading and investing decisions. We will learn about randomness, sampling variability, and data reliability. Today let’s look at randomness and the gambler's fallacy.

The real “secret” to making money in the market has to do with developing an edge in the market by using probabilities and proper money management. Unfortunately, people have trouble distinguishing between luck and skill when it comes to market predictions. We are unable to comprehend the many factors influencing an event as complex as the movement of a market. For example, if we had access to the number of buyers and sellers in the market at a given time plus information about the conviction and capital behind each trade, we would probably find the markets to be very predictable. Thus, any uncertainty you may have about how the market is going to behave at any given time is in you, not in the market. When you accept the fact that uncertainty is in you, rather than in the market, you will suddenly find you have much greater control over your own behavior towards the market. More importantly, you will have much greater control over the process of designing a trading system and greater understanding of how that trading system works.

When you develop a trading system, you are essentially deciding upon a set of judgmental shortcuts to help you make a decision. Yet people are completely unaware of how we make most of our predictions and judgments, let alone any biases in the way we make them. Thus, the process of designing a trading system is replete with error and becomes a very difficult process. In order to simplify the process, traders need to understand the following major factors: randomness, sampling variability, and data reliability.

Randomness. People want to treat the world as if they could predict and understand everything. As a result, one of the most significant biases people have is to seek patterns where none exist and to invent the existence of unjustified causal relationships. Traders don’t want to trade probabilities. They want consistency. For example, people fail to understand that a random sequence can include a long string or what would be called a trend. Instead, they try to understand the “trend” as something that it isn’t, instead of accepting that such phenomena occur.

Understanding and trading well are not necessarily the same thing. People don’t understand randomness, yet they expect to be able to understand the market. They then build trading systems out of their attempts to understand the market by identifying unjustified causal relationships without ever realizing they are doing it. It is this expectation to understand markets that leads traders to search for “Holy Grail” trading systems that explain the “underlying order” of the markets. There is nothing wrong with building a trading system based on microcosmic glimpses into how the market might work; but you need to know what you’re doing when you’re doing it. You are not trying to understand some mysterious underlying order in the markets. You are developing a set of rules whose long term expectancy gives you an edge in the market, while allowing you to withstand the worst possible catastrophe that could occur in the short term.

For example, many people observe a relationship in the market and assume it explains how the market works.

Jack noticed when a particular pattern occurred in the market, it frequently moved 50 to 100 points higher. He assumed the pattern meant that strong hands were moving into the market. And, when the market didn’t follow the pattern, he became very confused. I said, “How often, when you observe this pattern, does the market move like that?” He responded, “About 35% of the time!” Thus, Jack had simply observed a pattern that was quite profitable 35% of the time. The rest of the time it had no meaning.

A relationship may occur only 35% of the time, and that may be something you can make money with, but it has nothing to do with being right or trying to explain something. What you must learn is that most trading systems come out of observations that have a certain probability of being correct. Those observations do not explain anything. Remember, a trading system is just a set of rules to guide behavior, nothing less or nothing more. Apparent random fluctuations in the market are caused by many more factors than you can possibly monitor in your system.

Develop the attitude of following rules
because they give you an edge in the market.
Avoid the need to understand or explain the market.

Because people attempt to understand and make order out of the market, they assume that the longer a trend continues, the more likely it will suddenly turn around. More importantly, traders are usually willing to bet larger amounts of money on that assumption. Thus, traders want to pick tops and bottoms in a trend—a behavior that tends to be as dangerous as stepping in front of a moving freight train, hoping it will stop and turn around just for you. These biases are usually referred to as the gambler’s fallacy. They have resulted in the ruin of millions of traders over the ages. The gambler’s fallacy is one of those biases, which make trading difficult without a system and proper money management. However, traders frequently develop counter-trend following systems because of this bias—usually with disastrous results.

Double the Risk Double the Reward?

noreply@blogger.com (Williamk) — Tue, 20 Feb 2007 05:44:00 +0000

If you have a profitable trading system or method that risks, say, 2% of capital per trade based on your entry price and stop loss and makes 30% per year, then why not double this risk level and make twice as much return per year? This seems like a good idea until you think about the fact that doubling the risk does not necessarily mean you will double the return. Why? Here are a couple of things to consider:

Increasing risk per trade increases the risk of total loss. Imagine if your risk was 50% per trade, you would only need to have 2 losing trades in a row to lose 75% of your capital. As your chances of total loss increase, this has the effect of reducing your average ending equity in a simulation of the possible returns from your system and means that doubling up on risk may not double the average return you get.

Winning and losing are not symmetrical. If you lose 50% of your capital you have to have a 100% gain to get back to where you started. If you lose 75% (as in the previous example) then you have to have a 400% gain just to get back to breakeven.

With these examples is obvious that simply increasing risk does not always have a corresponding increase in return, and at some point your risk of ruin goes up significantly – in same cases to almost a certainty. This means you are taking on extra risk to such an extent that you are almost guaranteeing you will lose your capital.

My advice would be to simulate your trading with gradually increasing position sizing and make sure that you are trading at a risk level that does have a corresponding increase in average return that you are comfortable with - otherwise you are simply taking on more risk with little to show for it.

Paul King
PMKing Trading LLC
www.pmkingtrading.com

Take Control

noreply@blogger.com (Williamk) — Thu, 15 Feb 2007 14:58:00 +0000

In my mind, control is an important issue that has a great deal to do with
understanding the process of trading and doing it successfully. There many
parts of the trading process where exercising control is relatively easy and
other parts of the process where control is much more difficult. For
example, the entry into a trade is a point where we are very much in
control. We set the conditions and the market must meet our conditions or
we will simply refuse to participate. This is clearly the point in the
trading process where we can exercise maximum control.

I can recall attending some lectures many years ago by George Lane (of
stochastic indicator fame) when he revealed to the audience a list of items
that he wanted to see before he entered a trade. His pre-entry checklist
had twenty-seven conditions on it. Being a skeptic of complex trading
strategies I don't recall what any of these twenty seven items were except
I'm sure at least one of them was the stochastic indicator. At the point of
carefully reviewing his checklist George was very much in control of the
situation and if the market didn't do exactly what he wanted he didn't
trade.

As I often point out in my lectures, entries are the easy part of trading.
This is because each of us has maximum control at this point. We can
exercise as much or as little control as we like. George Lane can require
every one of his twenty-seven criteria and I can require my usual two setups
and a trigger condition. However the control situation changes drastically
once we enter the trade. Our ability to control all the elements of the
trade now becomes much more difficult and far from absolute. Once we enter
a futures trade we know that we must exit that trade within a limited period
of time or we are going to be in trouble because the contract will expire.
Even stock traders who don't need to be concerned about expiring contracts
must exit their positions correctly if they wish to maximize their profits.

Exits are much more difficult than entries because we can not simply reverse
the entry process and require that the market do thus and such. Once we are
in the trade George Lane and I can both throw our lists out the window
because we can no longer dictate our terms to the market. The market is now
in control and we must be prepared to react to whatever the market does.
The market can do anything it wants once we have entered our trade and we
can be assured that the market doesn't care what conditions might be on our
list or what our preferences might be. Once we enter the trade we are at
the mercy of the market the market operates according to its own list and
that list of possibilities is much larger than George Lane's meager list of
twenty-seven items. The market's options are limitless. It can do anything
it wants whenever it wants and somehow we must be prepared to deal with it.
Where is our control now?

As we hold our trade we must be prepared for big moves against us and big
moves in our favor. (Surprisingly the big moves against us are much easier
to deal with than the moves in our favor. We will talk more about this in
just a minute.) Among the market's limitless possibilities are gaps,
reversals, limit moves, whipsaws, and perhaps worst of all, boring sideways
action that makes us wish we were trading something else. The market may
present us with inside days, outside days, reversal days, key reversal days,
high volume days, low volume days, expanding ranges, contracting ranges,
acceleration, and deceleration. We can be faced with days that are so big
that the chart looks like a propeller on the end of a stick or days that are
so small they just look like dots.

Because we have to be prepared for all this and more, it should be no wonder
that our exit strategies are often much more complex than our entry
strategies. We need to have solutions ready for any problem the market
might send our way. As I mentioned earlier, the losses are rarely the
problem because we can control those by simply setting a loss point and
closing out the trade if the loss point is hit. Here again we are facing an
issue of control and it is comforting to know that we do have a great deal
of control over our losses. If we want to design a system where the average
loss is $487.50 it wouldn't be difficult. We can absolutely control the
size of our losses and we must be certain that we do.

All of our exit strategies have to be carefully planned to be certain that
we control what can be controlled. First we must recognize and understand
what can be controlled and then we must make certain that we exercise
whatever control we have. It may be comforting to know that we can strictly
control losses but it is extremely discomforting to realize that we have
very little control of our profits. If we have a $500 profit, how do we
make it become a $1000 profit? Unfortunately holding on to the trade longer
gives us no assurance that we will eventually have a $1,000 profit.

In this instance we have very little control but let's see what we can do
with the control that we do have. Although the amount of profits can not be
controlled in the sense of our somehow forcing them to be larger, they can
be controlled in the sense that we don't have to let them become smaller or
turn into losses. Those of you who have purchased any of our systems will
appreciate that locking in open profits at various levels is important to
the success of our trading strategies. You will notice that in the "25 X
25" Bond System (free on the web site) we use a very tight channel to help
lock in profits after twenty-five days or after five Average True Ranges of
profit. We can't control the market and force it to give us five ATRs of
profit, but if it does we can make sure that we keep most of it. Protecting
our open profits is definitely within our control.

When conceptualizing a new trading system and when going through the design
and testing routine, be alert to issues of control. Look for what you can
control and make sure that you are controlling it to your benefit. Look at
what you can not control and as a minimum have some plan that will minimize
any possible damage. Thinking about control will make you a better trader
and implementing control will make your systems trade better.

Chuck Lebeau is the co-author of Computer Analysis of the Futures Market, and the former co-editor of Technical Traders Bulletin. Chuck is currently operates a website devoted to trading topics; www.traderclub.com.

Trading Jokes

noreply@blogger.com (Williamk) — Sun, 11 Feb 2007 16:53:00 +0000

How a deal is done, selling short.

Jack, a smart businessman, talks to his son.

Jack: I want you to marry a girl of my choice

Son : “I will choose my own bride!”

Jack: “But the girl is Bill Gates’s daughter.”

Son : “Well, in that case…”

Next Jack approaches Bill Gates.

Jack: “I have a husband for your daughter.”

Bill Gates: “But my daughter is too young to marry!”

Jack: “But this young man is a vice-president of the World Bank.”

Bill Gates: “Ah, in that case…”

Finally Jack goes to see the president of the World Bank.

Jack: “I have a young man to be recommended as a vice-president.”

President: “But I already have more vice-presidents than I need!”

Jack: “But this young man is Bill Gates’s son-in-law.”

President: “Ah, in that case…”

This is how business is done!!

The St. Petersburg Paradox

noreply@blogger.com (Williamk) — Sat, 10 Feb 2007 15:04:00 +0000

Imagine a simple coin-tossing game where you get paid $1 if you toss heads on the first toss, $2 if you get heads on the second toss, $4 on the third toss etc. The mathematical expectancy of this game is:

1/2 times $1 + 1/4 times $2 + 1/8 times $4 etc….

This means the game has a minimum payout of $1 and an infinite expectancy. An interesting paradox arises because if the game has infinite expectancy then it would seem to be reasonable to pay any amount to play the game. In reality, this is not a good idea so the question that requires an answer is:

How much should one pay to play each turn of the game?

This simple game is known as the St. Petersburg paradox as first devised by Nicholas Bernoulli. It is discussed in William Poundstone’s Fortune’s Formula (which is #12 on our ‘Trader Must Read Top List’ by the way) and addresses the question by assuming that the game is impractical because no-one can actually offer an infinite payout. If one changes the game to be capped at say, $1 billion, then the expectancy is reduced to just under $16. To me this seems like a poor answer to the dilemma that ‘cheats’ by adjusting the rules of the game, and gives an answer that is still too high a price to pay for playing (based on common sense and ‘gut feel’).

Note that none of this is directly related to position-sizing since the game has a minimum $1 payout and no maximum payout – there is no chance of loss and the payout does not increase with the amount wagered. This is a case where position-sizing algorithms do not have a direct bearing on the problem since the ‘correct’ amount to pay for a turn is fixed.

I have found that many times in trading (and other games of chance or gambling), there is a gulf between mathematical theory and practical reality that can be effectively bridged by simulation. In this case if one simulates the game as described a large number of turns (10,000 for example) and takes the total amount won divided by the number of turns, this average win per turn will be a good indication of the practical true value of a turn.

The results I got from my simulations were that a turn was worth between $5 and $9, so if a casino offered this game I would play if it cost less than 5 times the minimum win of $1. If you used a geometric mean instead of arithmetic mean you would get an even more conservative (lower) estimated value of a turn.

So, how does this relate to trading? Well, one can think of the future price of any equity in terms of mathematical expectancy. If you estimate that an equity has a 50% chance of increasing 100% in value, but only a 25% chance of decreasing 40% in value, then if it is currently selling for $100, the future expected price is:

$100 + (0.5 100) – (0.25 40) = $140

Therefore one could buy the equity at the current price of $100 and expect to make a profit of $40. Of course, these calculations are always completely dependent on accurate estimation of the probability of future price increases or decreases, which is not an exact science like the probability of a coin toss coming up heads or tails.

In my opinion, making money at trading partly relies on a more accurate estimation of these kinds of probabilities than other market participants in order to find ‘inefficiently-priced’ equities to trade.

Paul King
PMKing Trading LLC
www.pmkingtrading.com

What Is A Robust Trading System?

noreply@blogger.com (Williamk) — Sat, 10 Feb 2007 15:04:00 +0000

With computer’s as powerful as they are today its easy to optimize a trading system and make it look exceptional. However, as we’ve already discussed, an optimized system is not a good system. Just simply because you're able to train your computer to have 20/20 hindsight does not mean it will perform anything like that in the future (neural networks etc.).

The primary problem with optimizing past performance is that markets change in the future. A low volatility market suddenly becomes a high volatility market. A market prone to trends becomes a choppy directionless market. A market that had high leverage has it margin changed and now it has low leverage. A regulated market suddenly becomes unregulated. The list is endless.

What tends to happen is that market X will tend to start acting like market Y and market Y will tend to start acting like market Z etc. If you have perfectly optimized the system to trade market Z then you will be in trouble when it starts to trade like market X! This is a problem with many systems, especially stock index systems that tend to be optimized to a single market or sector. In spite of their occasional awesome looking results there's a drop of poison in their mix.

Contrast the previous scenario with one in which the system has been designed to work well most all markets A thru Z. Now, it does not matter if market Z starts to act like market Y or market A starts to act like market P etc.. They can change as many times as they want because the system has been designed to be universally robust with most ALL the various markets! Once again, the market characteristics can reshuffle themselves countless times and your system is like a Swiss Army knife that has proven in historical testing it can deal well with most all of those scenarios.

There are a few tip offs to an optimized system.

Unrealistically good looking performance
Only trades one market or sector well
Uses different rules (algorithms) for each market
Uses different inputs for each market even if the rules are the same
Uses different rules or inputs for initiating buys vs. sells
Does not factor in realistic transaction costs (slippage & commission)
Uses money management methods that don’t include market normalization (like single contract performance only)
Uses static numbers for all markets like a $2000 stop or $5000 profit target (some markets could hit those in an hour and others could take weeks). This may seem to contradict #3 but it does not. Its ok if markets have different stops and targets etc. as long as they were all dynamically computed from the same algorithm and inputs (as opposed to a static predetermined number across the board).

An important feature of a robust system is that it should weight every market equally. The testing should have been done in such a way to “normalize” the difference between the markets. For example, natural gas changes an average of a few thousand dollars per day per contract, however, Eurodollars change an average of a few hundred dollars a day per contract. You need a way to balance and normalize this difference in testing.

The reason you need to do this is because what if the system meets most of the above non-optimized rules. BUT, its trading one natural gas market contract for every one Eurodollar contract? The system would look great if in the past it had a lot of natural gas winners. However, what it in the future natural gas starts to have a lot of losing trades and the Eurodollar starts to have a lot of winning trades? Do you think a number of hundred dollar winning trades in a single Eurodollar contract are going to be enough to offset a number of THOUSAND dollar losing trades in a single natural gas contract?

If your trading 20 markets its because you want diversification. However, if your trading them all on a single contract basis then your not really diversified. You might have 50% of your portfolio accounting for 90% of the profits and losses! The problem is that moving forward, you will be dependant on specific markets instead of just a certain percentage of the markets (regardless of which ones). Its far more robust not to be dependant on certain markets within the portfolio. No one market should be any more meaningful than any other one.

In summary a robust system should do the following

Trade a large portfolio of markets successfully
Trade that large portfolio successfully over a very long test period
Use the exact same rules for every market
Use the exact same input values for every market even if the rules are the same
Have the exact same logic and input values for initiating both buys and sells
Factors in realistic transaction costs (slippage & commissions)
Be tested in a way where the markets have been normalized for risk (not single contract)
Doesn't use Static preset exits for all markets IE $2000 stop or $5000 profit target for all markets, but rather dynamically computed ones.

After you have done all of this, the final step would be to do some walk-forward testing. This means, test and develop your system on data up until year 2000 (for example). Then after all the testing is done see how it would have done from year 2000 until now etc. This helps avoid a lot of the benefit of hindsight. All of these are things we have done in the development our systems.

Feel free to email or contact us with any questions or comments on this subject. dhoffman@traderstech.net

Trading Jokes: Cow Economics

noreply@blogger.com (Williamk) — Thu, 01 Feb 2007 22:44:00 +0000

TRADITIONAL ECONOMICS
You have two cows. You sell one and buy a bull. Your herd multiplies and the economy grows. You retire on the income.

INDIAN ECONOMICS
You have two cows. You worship them.

PAKISTAN ECONOMICS
You don’t have any cows, for you ate all of them and you do not know how to produce cow; You claim that most of Indian cows belong to you. You ask the US for financial aid, China for military aid, British for Warplanes, Italy for machines, Germany for technology, French for submarines, Switzerland for loans, Russia for drugs and Japan for equipment. You buy the cows with all this and claim of exploitation by the world. Eat the cows, you will be left with no Cows. Start the cycle once again, claim…

AMERICAN ECONOMICS
You have two cows. You sell one and force the other to produce the milk of four cows. You profess surprise when the cow drops dead, to give a scientific explanation, allocate research funding out of public exchequer, to find out what really happened.

FRENCH ECONOMICS
You have two cows. You go on strike because you want three cows. May be world can face another cow revolution.

GERMAN ECONOMICS
You have two cows. You re engineer them so that they live for 100 years, eat once a month and milk themselves.

BRITISH ECONOMICS
You have two cows. Teach them meat eating. Feed them dead sheep, so they grow hefty. Now, they are both mad cows.

ITALIAN ECONOMICS
You have two cows. You don’t know where they are. You break for lunch, eat Italian Veg Pizza.

SWISS ECONOMICS
You have 5000 cows, none of which belong to you. You charge others for storing them. Distribute secret codes, to establish ownership.

JAPANESE ECONOMICS
You have two cows. You redesign them so that they are one-tenth the size of an ordinary cow and produce twenty times the milk. You then create cute cartoon cow images called Cowkimon and market them worldwide.

RUSSIAN ECONOMICS
You have two cows. You count them and learn you have five cows. You count them again and learn you have 42 cows. You count them again and learn you have 17 cows. You give up counting and open another bottle of vodka.

CHINESE ECONOMICS
You have two cows. You have 300 people milking them. You claim full employment, high bovine productivity and arrest anyone reporting the actual numbers.

What is a Mistake?

noreply@blogger.com (Williamk) — Thu, 01 Feb 2007 22:41:00 +0000

It is easy to beat yourself up for making that ‘stupid losing trade’, but is that really a mistake if you followed your trading rules, entered when you should have, used the correct position size, added to or reduced your position size when you needed to, and exited when you should? Losing trades, weeks, months, and even years are a normal part of trading, and it is much more useful to define a mistake in a way you can a) detect it, and b) fix it so it should not happen again.

My definition of a trading mistake that needs to be identified and fixed is one of the following circumstances:

I did not stick to my pre-defined trading system, method, or rules
I discovered my trading business plan was incomplete or inconsistent
I chose (or was forced to) modify my trading rules intra-day
I traded when I did not pass my daily ‘self test’
I did not perform my daily, weekly, monthly, quarterly, or yearly review
I tried to blame someone or something else for a trading mistake

Note that none of these circumstances has anything to do with making a losing trade, or going through a drawdown. They are all to do with trading discipline and the procedural aspects of implementing your trading system accurately. In fact, I actually track the impact of my trading mistakes by calculating how much I actually made trading versus what my systems should have made if I had performed with 100% accuracy.

If you calculate this ‘error’ value as a percentage of your trading profit, you will have a ‘discipline score’ which tells you how much of a (usually negative when you are inexperienced) effect you are having on your trading implementation.

Note that blaming other circumstances for errors is a mistake in itself. For example, if your connection to your broker goes down and you can’t exit a position in time, this is your mistake for a) choosing the broker, b) choosing to trade, and c) not having a contingency plan and alternative broker for exactly this (common) situation.

If you pre-define what a mistake looks like, and take personal responsibility for them, and also put procedures in place for preventing the same mistake happening again, you will be a long way towards being a disciplined and accurate trader with a significant edge

Paul King
PMKing Trading LLC
Source: http://www.pmkingtrading.com

Systems - Buy Them Or Build Them?

noreply@blogger.com (Williamk) — Tue, 30 Jan 2007 17:56:00 +0000

Since we offer systems for sale one might assume that we would suggest
that systems should be purchased rather than built from scratch.
Actually we are very strong advocates of building your own system if you
are capable of doing so.

One of the reasons that we make this recommendation is that we believe
it is important that trading systems should fit the needs and
preferences of the user. A system may appear to have excellent
performance data but another trader may consider one trader's favorite
system as completely worthless. It seems that everyone has a different
level of comfort when it comes to following a particular system and the
comfort level increases dramatically if you are personally involved in
the planning and research that produces the system.

In addition to comfort levels and other psychological issues,
preferences for systems may vary because the resources of traders will
vary. For example some traders have very large amounts of capital to
work with while other may have much smaller amounts to put at risk. Due
to differences in capital or risk tolerances these traders may require
different systems. In addition to the amount of capital available there
are other resources that may influence the choice of systems. Some
traders have many hours a day available and want to trade for a living
while others have very demanding occupations and limited time to devote
to trading. Many systems traders have extensive experience with
computers and a great deal of knowledge about programming. But on the
other hand, many of us will have little knowledge and experience in this
technical field. Some systems traders have many years of actual trading
experience and others are admitted novices. Some traders have access to
the newest and most expensive hardware and prefer to receive real time
price data while many traders will find they can trade well using less
sophisticated equipment and simple end of day data.

We could continue with additional examples of important differences
among traders that might influence their preference in trading systems
but the point has been made. The advantages of building your own
trading system might be compared to the advantages of owning a tailor
made suit as opposed to buying one off the rack. If you build your own
system you can tailor it to your exact specifications so it fits your
preferences and resources.

However, just as most of us would not consider making our own clothing,
designing and testing a trading system is a task that may not be
appropriate or realistic for everyone. Assuming that you have the
necessary knowledge and resources to create your own system there are
still many obstacles to overcome. For one thing there is the
frustration of investing in equipment, software and data only to find
that most of our best ideas don't work. It would not be an exaggeration
to reveal that ninety nine percent of our research winds up in the
wastebasket. Also keep in mind the value of your time because until a
system is completed you will be working hundreds of hours for less than
minimum wages. There are no shortcuts so you had better enjoy the
entire process.

However the benefits of building the system yourself can be substantial
and we think the benefits are worth the effort. You will know and
understand the logic behind each step in the system. The knowledge
gained in the testing process should give you confidence in the system
so that you will have the necessary discipline to follow the system
correctly when it comes time to start trading it with real money. The
testing process should also give you a "feel" for the system that will
help you to sense when it is not performing as intended. If necessary
you will also have the ability to fine tune the system based on your
real time experience. We believe that over the long run the discipline
and confidence of the system operator have a great deal to with
determining the ultimate success of any system. By creating the system
yourself you are most likely to trust it and operate it correctly.

We suggest that you should seriously consider building your own systems
if you can satisfy most of the following criteria:

1. You enjoy challenges and have a knowledge of the commitment required
to excel at anything. If you have been an outstanding success at any
endeavor then you already understand commitment. In particular we
believe that success at competitive games like bridge, chess,
backgammon, poker and other pastimes requiring discipline, patience and
strategy would be a good indication that you can build a good system and
operate it successfully.

2. You own or are prepared to purchase a testing platform (like
TradeStation or something similar) and will spend the time required to
learn how to operate it.

3. You understand how to program the software you will be using or you
are willing to pay a professional programmer to assist you. If you do
not have a programming background you will find that there is nothing
easy about Omega's so-called Easy Language. If you have no programming
experience and decide to hire a programmer you should study enough about
the programming to enable you to communicate with your programmer. As a
minimum you need to be able to express your ideas in "if / then"
statements.

4. You need to have studied some basics on testing procedures and know
how to analyze and evaluate the test results. Some training in
statistical analysis would be very helpful.

5. You will need a source of clean historical data and the software to
convert the data to the format that will be used in testing. For
example you may want to convert the data to continuos back-adjusted
contracts. There are other popular formats for historical data and you
should know which format is appropriate for the testing and type of
system you will be creating.

6. You have spent some time clearly defining exactly what you want from
your system. You need to list and prioritize these desired
characteristics because they will guide your research.

7. You must have an abundance of time and patience. Picture yourself as
Thomas Edison setting out to invent the light bulb. Will you have the
commitment and patience to keep trying one element after another to find
the one that works? (As an example, we have been working on S&P trading
systems for years and we have yet to come up with one that we would be
willing to trade. We are still trying.)

8. Can you be truthful with yourself and analyze your test results
without letting your natural optimism cloud your judgment. (However, if
you are not an optimist you are automatically disqualified.)

Chuck Lebeau is the co-author of Computer Analysis of the Futures Market, and the former co-editor of Technical Traders Bulletin. Chuck is currently operates a website devoted to trading topics; www.traderclub.com.

TradEducation

Innumeracy

Is Trading Style Hard-Wired?

Mechanical Trading Systems

Successful Traders are Goal-Oriented, Disciplined, and Ambitious People

#The things that bring you joy can sustain you when things go badly.

#The things that bring you joy can give you a reason to succeed.

#The things that bring you joy give you the energy, enthusiasm and perseverance to keep going.

#The things that bring you joy combat depression and pessimism.

#The things that bring you joy make you a joy to be around.

#The things that bring you joy help you to think more creatively and more clearly.

#The things that bring you joy allow you to feel more joy in the things that normally do not bring you joy.

The mine field

Enter Sea Biscuit

True grit

Stray bullet of greatness

Conclusion

Back testing

Contents

What is a backtest?

The data mining problem

How to combat the data mining problem

Results of a backtest

How To Make A Million In 40 Trades

On Randomness and Streaks

A look At Optimization

Learning to Trade: The Psychology of Expertise

Expose Yourself! A Powerful Technique for Breaking Emotional Patterns in Trading

Being Overwhelmed and System Development Part 3

Perfectionism and System Development Part 2

Procastination and System Development Part 1

Do you Think Like a Trader?

Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part Three.

Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part Two.

Judgmental “Heuristics” Or Biases and Developing Your Trading System, Part One.

Double the Risk Double the Reward?

Take Control

Trading Jokes

The St. Petersburg Paradox

What Is A Robust Trading System?

Trading Jokes: Cow Economics

What is a Mistake?

Systems - Buy Them Or Build Them?