Quantifying Technical Analysis

Google has deleted all my blogspot images

2012-10-04T16:14:00.000-07:00

I started this blog as a way for me to document my trading experiments. I was doing very good till the point when Google started deleting my images. Apparently, the launched G+ and migrated all my images and lost it. I did continue with my testing of candle stick patterns... but I stopped uploading them

In the next little while with be re-generating this content and re-posting the results. Hopefully, I will be able to do this in a month or so

More about the Morning Doji Star

2011-01-27T13:26:00.000-08:00

Last month, I blogged that the morning doji star was a very rare pattern. I claimed that on an EOD basis, there are only ten instances of occurrence of this pattern in SP500 stocks over the last 15 years. The 10 instances are shown below. Of the 10 opportunities, 6 are profitable in the short term

1. AES on 10/30/1997

2. ETN on 4/23/1998

3. DHR on 10/5/1998

4. VNO on 10/12/1998

5. AMT on 7/13/2001

6. PX on 9/25/2001

7. LLL on 1/16/2002

8. PPG on 4/8/2002

9. CLX on 1/31/2005

10. VNO on 6/20/2005

Morning Star Doji : a mythical pattern

2010-12-23T14:25:00.000-08:00

The morning star star is shown on the left.

Quantifying the Morning Star Doji

Traditionally, a formed when the following conditions are met:

Prior to Day 1: a down trend exists. I characterize this be having three days with lower closes
Day 1 candle : Long and Dark. I have characterized this candle with a body that is atleast 65% of the candle length
Day 2 candle : This candle is the doji candle. The candle should gap down. The High of the candle needs to be less than the low of Day 1 candle. This is a doji, so the candle body should be less than 15% of the total candle length
Day 3 candle : This should be a white candle that gaps up. Since this is a white candle, the Close is higher than the Open. The Low of this candle should be higher than the High of the previous day candle

Problem with the Morning Star Doji

The definition of this pattern is actually quiet strict. I back-tested this pattern. In the last 15 years, there were less than 10 instances of this pattern. I was genuinely surprised and re-checked my runs. Same results.

I think the requirement between the requirement that there be a gap between bar1 and bar2 and another gap between bar2 and bar3 makes it an overly restrictive candle

Profitability of the bullish kicker candlestick pattern

2010-12-10T11:52:00.000-08:00

A bullish kicker is signal is shown on the left.

It shows a change in sentiment on what the buyers and sellers feel about the stock. The first candle is dark (close < open). I generally like see this red candle at the end of a trend. The bullish candle is the green candle (close > open) and the Low is greater than the previous candle's High. This usually marks a drastic change in sentiment regarding the stock. The traders before the green candle were pessimistic about the stock and the sellers were winning. They were successful in bringing the stock down. The kicker candle usually represents a change in sentiment and buyers are back. This may represent a positive announcement by the company.

Quantifying the Bullish Kicker

A bullish kicker is formed when the following conditions are met:

A down trend marked by three down days
The third candle has a close lower than open
The fourth candle open is greater than the high of the third candle
The fourth candle closes higher than the open

Back-testing Bullish Kicker

DataSet : SP500
BackTest Period : 15 years

Buy Signal :

Look for 3 consecutive down days
A Bullish Kicker candle is seen on the fourth day
Buy at Open on the fifth day

Sell Signal:

Limit order at 1.02 of the Entry Price
2% Stop Loas

Profitability / Performance of Bullish Kicker

Since I am only interested in finding out if this particular signal does act as a trend reversal signal. I am not interested in building a trading system. The best performance measure for this task is the Win-Rate as it represents the probability that my hypothesis is correct.

PERFORMANCE

Number of Trades	1,511	Winning Trades	825	Losing Trades	686
Average Profit %	-0.28%	Win Rate	54.60%	Loss Rate	45.40%
Average Bars Held	2.9	Average Profit %	2.18%	Average Loss %	-3.24%
		Average Bars Held	2.85	Average Bars Held	2.96

In the last 15 years there were 1511 instances of the bullish-kicker... that is about 100 every year. That is actually quiet good and sufficient to build a good trading strategy on. The win-rate was ~55%. Another way to look at it is that there is a 54% chance of making a 2% profit and a 45% change of losing 3%. If you did execute on every opportunity presented by this signal, you would have lost out in the end.

The number shown above are adjusted for commission (Interactive Brokers structure) and not adjusted for any slippage

Bullish Kicker Setup Example

Adjusting Yahoo Data

2010-11-09T10:09:00.000-08:00

In my previous post, I had explained that Yahoo and Google EOD (End of Day) historical data does not match.

Let us take a look at XOM. On 12/30/1994, Google reports the close price as $43.85. Yahoo reports the close price of $87.35 and also reports an adjusted close of $35.53. Y! adjusted close prices are adjusted for any splits and dividends. On the other hand, Google only adjusts for splits.

From a technical analysis point of view, I am usually not interested in the effects of dividends and am interested only in the split adjustment factor. Also, I prefer to use Y! EOD data as it is better in quality than Google data. It is more complete and is available for longer periods of time.To use Y! data, I would have to make some adjustments. The split-adjusted price can be calculated as follows:

split_adjusted_close (y') = split_div_adjusted_close(as reported by yahoo adjusted close)/div_adjustment_factor

To get the div_adjustment_factor, I need to look at all the dividend payouts. For XOM, the dividend table looks like:

Aug 11, 2010	$ 0.44 Dividend
May 11, 2010	$ 0.44 Dividend
Feb 8, 2010	$ 0.42 Dividend
Nov 9, 2009	$ 0.42 Dividend
Aug 11, 2009	$ 0.42 Dividend
May 11, 2009	$ 0.42 Dividend
Feb 6, 2009	$ 0.40 Dividend
Nov 7, 2008	$ 0.40 Dividend
Aug 11, 2008	$ 0.40 Dividend
May 9, 2008	$ 0.40 Dividend
Feb 7, 2008	$ 0.35 Dividend
Nov 7, 2007	$ 0.35 Dividend
Aug 9, 2007	$ 0.35 Dividend
May 10, 2007	$ 0.35 Dividend
Feb 7, 2007	$ 0.32 Dividend
Nov 9, 2006	$ 0.32 Dividend
Aug 10, 2006	$ 0.32 Dividend
May 10, 2006	$ 0.32 Dividend
Feb 8, 2006	$ 0.32 Dividend
Nov 8, 2005	$ 0.29 Dividend
Aug 10, 2005	$ 0.29 Dividend
May 11, 2005	$ 0.29 Dividend
Feb 8, 2005	$ 0.27 Dividend
Nov 9, 2004	$ 0.27 Dividend
Aug 11, 2004	$ 0.27 Dividend
May 11, 2004	$ 0.27 Dividend
Feb 9, 2004	$ 0.25 Dividend
Nov 7, 2003	$ 0.25 Dividend
Aug 11, 2003	$ 0.25 Dividend
May 9, 2003	$ 0.25 Dividend
Feb 6, 2003	$ 0.23 Dividend
Nov 7, 2002	$ 0.23 Dividend
Aug 9, 2002	$ 0.23 Dividend
May 9, 2002	$ 0.23 Dividend
Feb 7, 2002	$ 0.23 Dividend
Nov 7, 2001	$ 0.23 Dividend
Aug 9, 2001	$ 0.23 Dividend

For every dividend payout, I need to calculate a div_adjustment_factor. This is calculated as follows:

div_adjustment_factor = div/previous_close * previous_div_adjustment

For the Aug11 payout, the div_adjustment is :
div = $0.44
adjusted close on Aug 10 = $61.93
previous_div_adjustment = 1
div_adjustment = 0.44/61.93 = 0.007

When I make these calculation to the complete data set, I am able to match Y!EOD and Google EOD. I can then use this for any technical analysis work that I need to do

I have written a python script that download Y!data, adjusts it and saves it in a sqlite3 database. I can share this script with you, if you are interested. Drop me an Email at guru[at]kilotrader.com

DIfferences between Google Historical Data and Yahoo Historical Data

2010-08-12T17:00:00.000-07:00

In my search for a reliable source for historical data, I looked at many places. Some of the things that I was thinking about were :
- Data source needs to be free
- It should go back at-least 15 years
- It should be complete
- I should be able to download daily data and historical data in an automated way.
- Daily data should be available at 3pm every day

At this point I am only looking for OHLV data and NO fundamental data. The two places where I could free historical data were : Google and Yahoo. Unfortunately, the data is not the same. Take the following example,

Google quote: WMT for Jan 1, 1992, Close :$14.78
Yahoo quote: WMT for Jan 1, 1992, Close: $59.13, Adj Close: $12.32

So, Yahoo provides a quote for the end of day as it happened ($59.13) and also an adjusted close which makes and adjustment for any splits that happened on the stock. Google however adjusts for both splits and for any dividends that the company gave. So the numbers don't match.

Also, Google does not provide the Open price for the ticker. So it is incomplete

Historical Stock Price Data Source

2010-06-04T14:37:00.000-07:00

Most of the work that I do depends on EOD Data (end of day) data. At the end of the trading day, I like to download price/volume data for all the stocks in my universe, run my strategies, look for signals for the next day and place the buy/sell/stop orders before I go to sleep. This takes the stress out of trading and I really do not have to look at the screen all day and I can focus on my day job.

For this to work, I need to spend about an hour every day to plan my trades the next day. I simulate my backtests using Fidelity Wealth-Lab Pro. Fidelity does a very good job of delivering EOD historical data. But... they send the data over after 10PM at night. This leaves me very little time to plan my next day's trades. I would really like this data available at 3PM instead of 10PM

This led to do a search on what other sources of historical data are out there. This led me to this great article. I think it provides an awesome summary of the free data sources out there.

Yahoo and Google dominate the market. Yahoo provides more data than Google. Yahoo provides prices unprocessed and then adds an extra column for "split and dividend" adjusted close prices. You can then adjust the Open/Close/High/Low based on the adjustment ratios. Google provides data that is split adjusted and not dividend adjusted. So the Yahoo and Google data does not match up

Also, Google does not provide Open prices for before 1990. This is a setback and has kept me away from Google.

With the Yahoo data, I have written some C-sharp code to download the data and store it in an sqlite database. I hope incrementally build this database and use with Fidelity Wealth Lab for analysis

Kewl

Summary of Candlestick Backtesting

2010-05-19T08:00:00.000-07:00

This post summarizes the candlestick back-testing so far.

To understand the effectiveness / profitability of these signals, I choose to look at two measures of performance.

Number of Trades : The number of trades is number of times the particular showed happened during the back-test period. There are two inferences from this number:

If the number is small, the results are not statistically reliable.
The number provides an insight into the prevalence of the signal. This is important when building a system

Win-Rate : The win rate represents number of times this particular signal was profitable. Looking forward, this can be thought of the probability that this signal will be profitable

The back-tests were done on the SP500 symbols over the past 15 years.

Pattern	Win-Rate	Number of Trades
Doji	52.72%	3403
Bullish Engulfing Pattern	45.60%	6268
Bullish Harami	47.87%	3787
Hammer	46.71%	2387
Bullish Kicker Pattern	54.6%	1511

Backtesting the Bullish Harami Pattern

2010-05-18T08:00:00.000-07:00

This is the third post in my three part series of backtesting a candlestick patterns. Earlier, I back-tested the Bullish Engulfing Pattern and the Hammer. Today, I will back test the Bullish Harami Pattern.

Quantifying the Hammer

A Bullish Harami pattern is formed when all the following conditions should be met :

today's bar is white (up day) and yesterday's bar is dark
today's candle height is less than yesterday's candle body

Back Testing the Pattern

DataSet : SP500
BackTest Period : 15 years

Buy Signal :

Look for 3 consecutive down days
A Bullish Harami is formed on the third day and the fourth day
Buy at Open on the fifth day

Sell Signal:

Sell on the sixth day

Performance

I am only interested in finding out if this particular signal does act as a trend reversal signal. I am not interested in building a trading system. The best performance measure for this task is the Win-Rate as it represents the probability that my hypothesis is correct.

PERFORMANCE
Number of Trades	2,387	Winning Trades	1,115	Losing Trades	1,272
Average Profit %	-0.27%	Win Rate	46.71%	Loss Rate	53.29%
Average Bars Held	2	Average Profit %	2.54%	Average Loss %	-2.73%
		Average Bars Held	2	Average Bars Held	2

Setup

Backtest the Hammer

2010-05-17T11:43:00.000-07:00

This is the second post in my three part series of backtesting a few candlestick patterns. Earlier, I back-tested the Bullish Engulfing Pattern. Today, I will back test the Hammer.

Quantifying the Hammer

A Hammer pattern is formed when all the following conditions should be met :

today's bar is white (up day) followed by three down days
Candle's body height is less than 40% of the total candle height
Close is located near the top of the candle

Back Testing the Pattern

DataSet : SP500
BackTest Period : 15 years

Buy Signal :

Look for 3 consecutive down days
A Hammer candlestick is formed on the fourth day
Buy at Open on the fifth day

Sell Signal:

Sell on the sixth day

PERFORMANCE
Number of Trades	3,787	Winning Trades	1,813	Losing Trades	1,974
Average Profit %	-0.21%	Win Rate	47.87%	Loss Rate	52.13%
Average Bars Held	2	Average Profit %	2.68%	Average Loss %	-2.86%
		Average Bars Held	2	Average Bars Held	2

Setup

Backtesting Bullish Engulfing Pattern

2010-05-15T08:00:00.000-07:00

In my blog post yesterday, I said that I will be back testing three candlestick patterns. Today, it is the Bullish Engulfing Pattern.

Quantifying the B-E Pattern

A Bullish-Engulfing pattern is formed when all the following conditions should be met :

today's bar is white (up day)
yesterday's bar is dark (down day)
today's trading range is larger than yesterday's
today's close is greater than yesterday's open

Backtesting the pattern

DataSet : SP500
BackTest Period : 15 years

Buy Signal :

Look for 3 consecutive down days
A Bullish-Engulfing candlestick is formed on the fourth day
Buy at Open on the fifth day

Sell Signal:

Sell on the sixth day

PERFORMANCE
Number of Trades	6,268	Winning Trades	2,858	Losing Trades	3,410
Average Profit %	-0.37%	Win Rate	45.60%	Loss Rate	54.40%
Average Bars Held	2	Average Profit %	2.56%	Average Loss %	-2.83%
		Average Bars Held	2	Average Bars Held	2

In this particular example, there are two things I would like to note :

Bullish Engulfing patterns happen quite often. For the SP 500 stocks in the last 15 years, they showed up about 400 times in one year
They are NOT very good at predicting a trend reversal. For the SP 500 stocks in the last 15 years, they were correct only 45% of the time

Buy Setup

More on Candles

2010-05-14T13:00:00.001-07:00

My recent forays into candlestick patterns has not been very encouraging. I tested the doji as a trend reversal signal and the results were not impressive.

On doing some more research, I came across candlestickgenius.com. They claim to be fairly successful at spotting candlestick pattern and have a description on the most reliable candlestick patterns. In the next few posts, I will be testing three of these patterns and presenting the results.

Bullish Engulfing

Bullish engulfing pattern is formed when

today's candle is taller than previous day's
today's candle body is taller than previous day's
today's candle is white and the previous day's is black

Hammer
A hammer is formed when:

today's candle is white
today's candle body is short in relation to the candle height
today's candle body is located near the top of the candle

Bullish Harami Pattern
A bullish harami is formed when:

today's candle is white
previous day's candle is dark
today's candle is shorter than previous

Do Candlestick Patterns Work ?

2010-05-13T12:29:00.000-07:00

Recently, I have been exposed to a lot of material on candlestick charts (Japanese Candlestick Charting Techniques, Candlestick Forum). I really like the intuitive look and feel of a candlestick charts.

Generally speaking, quantitative trading and chart patterns do not work well together. Candlesticks make it easier. In candlestick parlance, a doji is formed when a security closes very near its open price. From a quantitative perspective, I could spot a doji as follows :

Doji as a trend reversal signal

Conventional wisdom states that the doji is a trend reversal signal. It signals a 'draw' between the buyers and sellers. If a doji shows up at end of consecutive down days, it may mean that the down trend is coming to an end.

Back testing the Idea

Let us back test this idea. I will set up my test as follows :

DataSet : SP500
BackTest Period : 15 years

Buy Signal :
Condition 1 : Look for 5 consecutive down days
Condition 2 : A doji is formed on the sixth day

Buy At Open on the seventh day

Sell Signal:
Sell on the eighth day

Buy Setup

BackTest Results
Net Profit	($7,782.10)	Number of Trades	3,403
Profit per Bar	($1.14)	Average Profit	($2.29)
Total Commission	($13,612.00)	Average Profit %	0.04%
		Average Bars Held	2

Winning Trades	1,794	Losing Trades	1,609
Win Rate	52.72%	Loss Rate	47.28%
Gross Profit	$152,433.90	Gross Loss	($160,216.00)
Average Profit	$84.97	Average Loss	($99.57)
Average Profit %	2.69%	Average Loss %	-2.92%
Average Bars Held	2	Average Bars Held	2
Max Consecutive Winners	36	Max Consecutive Losses	18

The theory is impressive. The name of the signal is impressive. The back test results are NOT. And this leads me to question. Do candlestick patterns work?

Performance Metrics - resonance

2010-05-13T08:00:00.000-07:00

Recently, I blogged about Performance Metrics. My friend at Engineering Returns agrees with me.

I am not sure if the author has ranked his KPIs in ascending order of importance. But if he did, his top three metrics match with my top three.

A Price Action Based Strategy

2010-05-11T16:00:00.000-07:00

The use of price action to make buy/sell is prevalent. According to many, price action is the fundamental thesis of practitioners of technical analysis. Technical Analysis is the art of following price action.

I am presenting back test results for a simple price action based strategy. This is a "long-only" strategy

BUY SIGNAL
- If price goes down for three consecutive days
- If ATR (Average Trading Range) is lesser for three consecutive days

TYPICAL SETUP
A entry typical is shown below:

BACK TEST RESULTS

DataSet : SP500
Period : 15 years

	Long Trades
Net Profit	$18,457.37
Profit per Bar	$5.41
Total Commission	($6,640.00)

Number of Trades	1,660
Average Profit	$11.12
Average Profit %	0.26%
Average Bars Held	2.06

Winning Trades	982
Win Rate	59.16%
Gross Profit	$69,689.33
Average Profit	$70.97
Average Profit %	1.88%
Average Bars Held	1.95

Losing Trades	678
Loss Rate	40.84%
Gross Loss	($51,231.96)
Average Loss	($75.56)
Average Loss %	-2.09%
Average Bars Held	2.21

Maximum Drawdown	($2,383.78)

Profit Factor	1.36
Recovery Factor	7.74
Payoff Ratio	0.9

It is amazing to note a simple strategy as stated above,
- has a win rate of 60%
- is profitable over a long period of time

Performance Metrics

2010-05-03T18:11:00.000-07:00

"What Gets Measured Gets Done"

Over the past few weeks, I have been thinking about how to measure the success/failure of my trading strategy. I wrote a post titled, What is a good strategy. I have also been looking what other people are doing with respect to performance metrics of a strategy.

Stockalicious claims to the the Worlds Easiest Portfolio Analysis tool. It sure is easy. I uploaded my trades saved in a csv format and it gave me the following metrics

Total Return
Maximum Return
Minimum Return
Annualized Return
Volatility
Sharpe Ratio
Max DrawDown
Max Cost of Capital
Max Equity

On top of these measures, I think there are two other important measures: CAGR and Win Ratio. The Win ratio is easily calculated. It is the ratio of

CAGR stands for Compound Annual Growth Rate. I think it gives the most accurate way of comparing two strategy by normalizing time over an year. It can be calculated as shown below

A portfolio that has a rate of return of 1% over 4 trading days has a CAGR of ~85%. Another portfolio that has a rate of return of 5% over 20 trading days also has a CAGR of ~85%. Gains of 1% over 4 days may be more achievable that gains of 5% of over a month.

Another important metric is the Max Drawdown as a measure of risk to the portfolio. This is a measure of the difference between the highest value of the portfolio to the lowest value of the portfolio. A very high drawdown can make the strategy impractical as you may not the capital to execute the on the signals provided by the strategy.

I think that these three measures (win ratio, cagr and draw down) are the most important of all the performance measures out there

Relatively Speaking !!

2010-04-27T14:23:00.000-07:00

I just finished reading this book called Beat the Market: Invest by Knowing What Stocks to Buy and What Stocks to Sell by Charles D. Kirkpatrick. This book has resonated with me quite a bit. Needless to say, I highly recommend it.

The book presents the authors research where is looks at the market in relation to itself and introduces the concept of relatives. The author compares the performance of the stock in relation to the other stocks in the market and ranks them in percentiles. He then 'backtests' and claims that the 'market leaders' continue to lead the market in the short term and yield better than the market.

Sounds good to me. It is a simple idea that makes sense.

What is a good strategy ?

2010-04-23T17:19:00.000-07:00

In my last post, I showed a very simple strategy. Of course it does not work in the real world. It exposes too much of your capital to risk... capital that is better used elsewhere.

So, that leads to me to the question of this post. What is a good strategy. The strategy in the last post was profitable. Over a span of 5years, it yielded 11%. On an annualized basis, its gave 2.21 % per year. It is definitely not fantastic, but is better than your bank.

Notice that the win rate for that strategy was 40.48 %. I could think of this number as probability of being successful in my next trade. Another way to state this is : I made a profit of 19.27% for 40.48% of my trades and I took a loss of 9.16% for 59.25% of my trades. This gives me an average profit of 2.35% / trades. An average trade was 127 bars long (~ 3 months).

The goal of a good strategy is to get the best returns with the smallest risk. So, a desirable strategy would have :

A high average profit number
A high win rate
A low average barsHeld number (trade length)

Is there such a strategy out there?

A simple Moving Average Based Strategy

2010-04-16T17:19:00.001-07:00

Let us take a look at a very simple moving average based strategy. This strategy is discussed in Beyond Technical Analysis

STRATEGY RULES :

Rule 1 : Go LONG at next days' open if 3-day SMA crosses over 65-day SMA

Rule 2 : Close LONG position and Go SHORT next days' open if 3-day SMA crosses under 65-day SMA

Rule 3 : Cover SHORT position. Back to Rule 1.

Since moving averages are lagging indicators of trend, rule 1 indicates in the last three days, the short-term price action for the
security is positive and it may be time to jump in.

This strategy is an long/short strategy is always takes a position. There is no "time-out" period. You are either long or
short with the security.

The back test results are shown below. The strategy was back tested on 5 year data with S&P 100 stocks

	All Trades	Long Trades	Short Trades	Buy & Hold
Starting Capital	$10,000.00	$10,000.00	$10,000.00	$10,000.00
Ending Capital	$11,151.13	$11,326.72	$9,824.41	$12,685.16
Net Profit	$1,151.13	$1,326.72	($175.59)	$2,685.16
Net Profit %	11.51%	13.27%	-1.76%	26.85%
Annualized Gain %	2.21%	2.53%	-0.35%	4.88%
Exposure	54.66%	24.41%	30.89%	79.77%
Total Commission	($55.50)	($33.96)	($21.54)	($4.90)
Return on Cash	$0.00	$0.00	$0.00	$0.00
Margin Interest Paid	$0.00	$0.00	$0.00	$0.00
Dividends Received	$0.00	$0.00	$0.00	$0.00

Number of Trades	620	404	216	95
Average Profit	$1.86	$3.28	($0.81)	$28.26
Average Profit %	2.35%	3.80%	-0.38%	32.62%
Average Bars Held	127.37	86.60	203.61	1,238.99

Winning Trades	251	162	89	62
Win Rate	40.48%	40.10%	41.20%	65.26%
Gross Profit	$3,935.18	$2,500.72	$1,434.46	$3,470.93
Average Profit	$15.68	$15.44	$16.12	$55.98
Average Profit %	19.27%	18.52%	20.62%	65.73%
Average Bars Held	204.39	156.62	291.35	1,229.94
Max Consecutive Winners	14	14	12	6

Losing Trades	369	242	127	33
Loss Rate	59.52%	59.90%	58.80%	34.74%
Gross Loss	($2,784.05)	($1,174.00)	($1,610.05)	($785.77)
Average Loss	($7.54)	($4.85)	($12.68)	($23.81)
Average Loss %	-9.16%	-6.06%	-15.09%	-29.57%
Average Bars Held	74.97	39.73	142.12	1,256.00
Max Consecutive Losses	16	19	19	3

Maximum Drawdown	($1,846.04)	($854.87)	($2,264.80)	($6,304.03)
Maximum Drawdown Date	10/28/2009	7/7/2009	4/14/2010	3/9/2009
Maximum Drawdown %	-15.20%	-7.87%	-18.73%	-43.94%
Maximum Drawdown % Date	10/28/2009	7/7/2009	4/14/2010	3/9/2009

Wealth-Lab Score	3.43	9.55	-1.36	3.43
Sharpe Ratio	0.22	0.40	-0.20	0.35
Profit Factor	1.41	2.13	0.89	4.42
Recovery Factor	0.62	1.55	0.00	0.43
Payoff Ratio	2.10	3.06	1.37	2.22

Moving Averages

2010-03-18T13:29:00.001-07:00

Moving Averages are the most widespread of technical indicators that are used in trading equities, futures and currencies. Arguably, they are the most successful of the indicators that are out there. At the very least, they are as good as any other indicator. They are really easy to understand and implement. Maybe, that explains the popularity.

As a beginner, it is vital to understand moving averages. We need to understand what they are and how they behave and how profitable they really are. Over the next few posts, I intend to explore this very simple concept and test MA based trading strategies.

Simply stated a moving average is the average value of the last n days of trading. Since this value is different for every trading, it value is 'moving' with time. Plotted against the time axis, it provides smoothed version of the time series under consideration (close, high, low).

Shown above are two moving average curves for COST. In the picture shown above the arithmetic average is used to give us a Simple Moving Average, SMA. You could also use a linearly weighted average (Linear Weighted Moving Average, LMA) or an exponentially weighted average (Exponentially Weighted Moving Average, EMA).