A bear market is defined as a peak-to-trough decline in the S&P 500 Index of 20% or more. The bull run data reflect the market expansion from the bear market low to the subsequent market peak. All returns in the table are S&P 500 Index returns and do not include dividends. The table assumes the current bull run from 3/9/09 through 12/31/11. It could be argued that the index had a bear market in the decline of 2011.

The good news is that cyclical bear markets haven't historically been permanent losses for this stock market index. The losses were eventually recovered in about 2.2 years. This time, however, the bear market has lasted 4 years and 4 months. It could be argued that the this index barely reached its 2000 peak in 2007, so it has actually traded in a range below the current level for more than a decade. To see what I mean, read: S&P 500 Index Inflection Points of the Current Secular Bear Market. Clearly, buy and hold may be a risky investment strategy for individual investors who don't have unlimited time horizons. You can probably understand why a tactical strategy that aims to avoid some of the loss and capture some of the gains has become very popular in recent years. As wealth managers often point out: the trouble is that few investment managers have any skill or experience actually doing it. And, many of them who have actually been doing it long enough to speak of haven't done it very well. 

Source: Standard & Poor’s, FactSet, J.P. Morgan

Source: Standard & Poor’s, First Call, Compustat, FactSet, J.P. Morgan Asset Management.

Dividend yield is calculated as the annualized dividend rate divided by price, as provided by Compustat. Forward Price to Earnings Ratio is a bottom-up calculation based on the most recent S&P 500 Index price, divided by consensus estimates for earnings in the next twelve months (NTM), and is provided by FactSet Market Aggregates. Returns are cumulative and based on S&P 500 Index price movement only, and do not include the reinvestment of dividends. Past performance is not indicative of future results.

CSFB examines the dynamics and impact of inflation and currency risk and how stocks and bonds have performed in different conditions. Inflation erodes the value of most financial assets, though some assets like gold or homes may actually rise in price. After all, inflation is generally “rising prices” of things (like homes). Stocks may be negatively impacted by rising inflation, but to a lesser extent than bonds or cash. Investment salespeople often promote stocks as an inflation hedge, but stocks may actually only offer limited hedge against rising inflation and that’s due to their higher ‘expected’ return, not because they rise with inflation.

The currency section speaks of how changes in exchange rates can boost or lower the return of foreign investments, such as global or International ETFs.

The various impacts of inflation, currency, etc. is a topic that John Murphy covered very well years ago in Intermarket Analysis. It’s useful to have an understanding of how different assets typically respond to changing conditions. It’s also useful to have historical data so you actually know the probability and can develop an expectation. Therein lies the potential for trouble: when you develop an expectation of something you may create a hope for things to turn out a certain way. If your expectations are strong, you may worry about it and then be upset when it doesn't turn out the way you expected. Or, if your expecation is very strong you may bet heavy on that outcome and the more confident you are, the less adaptive you'll likely be to change when the condition changes. What we learn from past data is that, while things probably play out a certain way, it is rarely all the time. After all, that's why it's 'probablistic'. If you are positioned for a certain outcome, you may be on the wrong side of reality if you aren’t adaptive.

After reading over Credit Suisse Global Investment Returns Yearbook 2012, I find some of the data may be useful knowledge. But at the end of you day- it makes me grateful that I have a system for buying and selling that adapts to changing price trends. I don’t need to know in advance if inflation will be high or if instead the condition will be deflation. I don’t need to know if a change in currency will impact my foreign stock exposure. I don’t need an indicator to tell me if others are “risk on” or “risk off”. None of these things are known for sure in advance. Even if you know how an asset typically reacts to a certain condition, you still don’t know it will this time. No one knows in advance which condition will play out. The best anyone can do is adapt. All of these things are reflected in the direction of the price. If they aren't, then they don’t matter.  If the condition does impact the price of our positions, my system will respond to it. That, I’m sure of. It’s what it does. If we are going with what is rising in price, we may end up with those things that are responding to underlying conditions. If we do that profitability over a long time, then we increase our odds that we outpace the erosion of our buying power due to inflation. 

These are the best possible activities we can do.

I find that many things initially seem to be in conflict. On the one hand, we need to quantify things to determine probability and to make good decisions. On the other hand, there are many issues with quantifying and discovering the real probability. Those who do it best are well aware of the paradoxes. As with anything, doing something doesn't necessarily mean you do it well. Once we figure out what to do, we have to do it well. 

On this Super Bowl Sunday, all the math and science is present, though even those who quote it the most seem unaware of how it works. Ah, there is another paradox. For everyone I know who doesn't have any real understanding of probability and statistics at all I probably know another whose mind is full of so much math they are unable to apply it in the real world. I learned my most useful math on my own and I think that’s been an advantage. First, I did it because I wanted to, not because I needed a grade. Then, I really needed to know it to apply it in my portfolio management systems, not just to score on a test. That may be a disadvantage for those who learned even at the most Ivy of leagues. Intentions can make all the difference. 

The paradox today is about how college football ranking leads to a Super Bowl, or not.

Earlier this week I pointed out how the National Signing Day for college football gets a lot of press based on the rating agencies. The school who happens to attract the most top ranked recruits will get the most media attention for having the top ranked class. Yet, the ranking is based on what another organization believes the rating should be. It has nothing to do with a individual programs own proprietary rating of how they believe that player may fit within their program. The paradox is; on the one hand, the rating agencies quantify the talent and skill and that's at least the right intent, on the other hand their methods may not actually be accurate or useful. Or, it may simply not be useful to an individual football program. 

Waiting around for the Super Bowl today, I thought I’d check to see how football programs ended up on Rivals.com recruiting class ranking. Steve Megargee, a Staff Writer at Rivales.com wrote a excellent story titled "Super Bowl rosters filled with underdog stories". (I just noticed that he is up the road in Brentwood, Tennessee). In it, he said:

Half the Patriots who came up during the Rivals.com era weren't five-star, four-star or even three-star prospects. Eleven of those 36 players signed with FBS programs as two-star recruits. The remaining seven either began their college careers as walk-ons or enrolled at non-FBS programs. 

Now they're heading to the Super Bowl.

So even though the Patriots enter this game as slight favorites, they actually are the Super Bowl team with the most underdog stories.

Judgemental heuristics are a "rule of thumb". People naturally want to make quick decisions and judgements, so they draw from what they know. If we know enough of the right things, we can have 'expert intuition' and our 'rules of thumb' may be useful, at least initially. 

I enjoyed the article because it pointed out that many of the players on the field in tonight's game weren't ranked as top recruits in the early stages of their career. Still, you may consider that the title of the article still called them "underdogs". You can probably see how judgemental heuristics can stick with us that way. Would we consider them an "underdog" just because some rating agency hadn't ranked them high so many years ago?

There are no underdogs in tonight's game. That's why they all get a ring.

His tweet was right on:

Patriots get five-star results from players who were two-star recruits (or less).

If a future date isn't yet here, now, in the present, in this moment, then it doesn't yet exist. 

So, if you really believe you or anyone could know, then you necessarily believe they have the ability to pass into the future while everyone else stays here, in this moment. If you or someone you know can really do that, then you probably know the outcome of the Super Bowl. 

Or, maybe you are one of the lucky few who gets tomorrow's newspaper? If you can get it in advance, then you will know the outcome today. If you can jump forward in time, get the paper, then come back here, now, then you'll know the winner. That's all we need to do.

And, we only need to know once. 

If we can be sure we know the outcome, the winner of the Super Bowl, or the price move of a stock or commodity, we only need to be sure one time. If someone is certain, then they could guarantee it. They could make billions if they do it just once. They could leverage it by borrowing all the money they can. I've heard people say they believe large investment banks like Goldman Sachs either know the future or controls it. If they did, they could guarantee it and take a cut. It would only take once. If they know for sure just one time, that's all it would take. Put trillions of dollars behind that one time and be done. The truth is, we can know the probability and probabilities by definition aren't a sure thing. Probabilities play out over many different flips of the coin. We can't bet too much on any one because we aren't sure. We don't need to be. But guessing the winner of Super Bowl XLVI - you get only one guess. If you really know, if you're certain, that's all you need.

Still, someone reading this still believes someone knows the outcome of the Super Bowl in advance. Maybe it's rigged. Someone once told me the Steelers would win because the Mob controls it and they own the Steelers. He really believed that. They lost. 

There are analysts who really spend a lot of time and effort trying to predict who will win. Just as they try to predict what stock will be the winner. They know a lot about all the players and how they match up against the other team. They know about the coaches and their playbooks. You can know a lot going in to the game. Then, the chaos begins. The star gets hurt of the coach pulls out a totally different playbook you were unaware he had. You were unable to predict all the things that may go differently that you expected and that path that would take things. In fact, the winning team will probably be the one that adapts to the conditions the best. The same is true in portfolio management. 

Someone may still be reading this, hoping I'm going to admit that I do have tomorrow's newspaper and tell the winner. They want to know a Savant. 

The truth is, I don't know. Even if I did, it would take away all the fun of not knowing. Watching the game play out is far more fun when you don't know. If you have expectations, you'll be disappointed if it doesn't all play out that way. Will it be Tom Brady and the Patriots or Eli Manning and the Giants? 

We'll see...

For it is in the essence of his behaviour that he should be eccentric, unconventional and rash in the eyes of average opinion. If he is successful, that will only confirm the general belief in his rashness; and if in the short run he is unsuccessful, which is very likely, he will not receive much mercy. Worldly wisdom teaches that it is better for reputations to fail conventionally than succeed unconventionally.

-- John Maynard Keynes 

Mediocre: of only ordinary or moderate quality; neither good nor bad; barely adequate.

Eccentric: deviating from the recognized or customary character, practice, etc

Unconventional: not bound by or conforming to convention, rule, or precedent; free from conventionality

Source: Rivals.com

College football National Signing Day is the first day that a high school senior can sign a binding National Letter of Intent for college football with a school that is a member of the NCAA, the main governing body for college sports in the United States.

National Signing Day has become a phenomenon. The athletes get their 15 minutes of fame. Football coaches lobby hard for top ranked recruits to sign with their program. Some will do anything to get a recruit. 

At the end of the day, the media will focus on what program 'won' the contest: who recruited the top ranked class. The rank of the athlete, a one star to a five star, is conducted by outside services like Rivals.com. Rivals then ranks the overall signing class, based on the sum of all the individual ranks. 

At the end of the day, a program will be ranked based on what some outside source thinks of the recruiting class, irregardless of how those individual recruits fit within the program. And, that is what will get the attention. 

That may sound familiar.

As with portfolio management, people are often focusing on the wrong things. I find that most people don't even know how the ranking services quantify the ranking. Is it qualitative? Is it quantitative? Or, is is some combination? I believe the best coaches and football programs operate their own proprietary ranking system based on the factors they believe are most important. 

It reminded me of a phone call I got from a wealth manager around March 2009. She wanted me to talk to her client whose account had declined from around $10 million to around $3 million due to losses. The investor had sold a business and was withdrawing about $500,000 annually for a lively retirement. That's about 5% on $10 million. But it's a dangerous amount on $3 million, especially when the value was still declining and no one knew how much more it would. Her client was starting to panic. All of the money was invested in high dividend paying stocks. Guess which sectors pay the dividends? Financials like banks and Real Estate Investment Trusts. You probably know what happened to them.

I thought I would point out the price chart of the Dow Jones U.S. Select Dividend Index over the most recent full market cycle. The chart includes the return of both price and dividends. You may notice what I did: it looks like the typical stock index roller coaster, if you bought and held it. While there are times when high dividend stocks are leaders and trend positively, they are not immune from the downside. 

The chart below represents nearly 7 years. You may notice where it ended and the path it took to get there.

Source: Stockcharts.com

I couldn't help from noticing the size of that decline from the 2008-2009 cascade, so I thought I would point it out. It was about -60%, even more than the S&P 500 stock index. If you want to measure the magnitude of the possibility of a loss, it's the worst historical draw-down. I think we could say the size of the potential loss, then, is -60%. I think we have quantified the answer to my question in the title. You can decide for yourself. What you believe will be true for you. It seems that dividend paying stocks are just like any other factor: their risks need to be managed, not ignored. There is a time for them and a time to avoid them. 

Source: Stockcharts.com

For an even longer term view, below is the 10 year chart taken directly from the Dow Jones U.S. Select Dividend Index website:

Source: Dow Jones Indexes

They said:

Severely depressed real estate prices continue to be a concern for investors. For some perspective on the magnitude of the decline in home prices, today's chart presents the median single-family home price divided by the price of one ounce of gold. This results in the home / gold ratio or the cost of the median single-family home in ounces of gold. For example, it currently takes a relatively low 105 ounces of gold to buy the median single-family home. This is dramatically less than the 601 ounces it took back in 2001. When priced in gold, the median single-family home is down over 80% from its 2001 peak, remains well within the confines of a six-year accelerated downtrend and remains very near its 1980 trough.

I believe, based on empirical quantitative evidence, that marny market prices tend to trend asymmetrically: they decline faster than they rise. It's probably because investors respond to negative news and losses differently than they do good news and gains. As we see in the chart, home prices fell asymmetrically, they increased for 20 years and only took 10 years to erase those gains.

During the secular bear market of the 1960's and 70's, home prices decline along with stock prices. Gold increased in price. You may recall that gold was a popular investment in the early 1990's. Of course, that was 'after' gold had already gone up. You may notice the cost of a single family home priced in gold is near the low in 1980. Some people may look at the chart and conclude that it's at the 'low', but that assumption would be based only on one data point. Statistical significance requires many more to draw inference about the future. Though, this is such a long term trend unfolding that, for all we know, it very well could be one indication that the secular bear market may be closer to its end. Since you don't know, nor does anyone else, you can probably see why it's important that our investment management programs that pursue an asymmetric risk/reward profile be adaptive to changing directional trends. 

Home prices decline for third consecutive month 

Los Angeles Times - 18 minutes ago

By Alejandro Lazo Home prices in the nation's biggest cities fell for the third consecutive month in November, a sign the housing market ended 2011 in a weakened state.

Home prices post steep decline in November   CNNMoney

Home prices drop in November for third straight month   USA TODAY

The top headlines, according to Google Finance, are news about a drop in home prices. One of them said home prices in the nation's biggest cities fell for the third consecutive month in November. 

They are speaking of the Standard & Poor's/Case-Shiller index which measures the residential housing market, tracking changes in the value of the residential real estate market in 20 metropolitan regions across the United States. The Standard & Poor's/Case-Shiller index showed price declines in 19 of the 20 cities it tracks in November – the second month in a row that nearly every city in the index was in negative territory. 

Apparently, news about November is just now coming out the last day of January.

Funny thing, because below is the price chart of the Dow Jones U.S. Select Home Construction Index. It's an index that tracks the prices of a group of publicly traded home builders. The home builder related stocks have been in a positive trend during the period mentioned in today's news. In fact, its trend has been strengthening against other sectors. 

Source: http://stockcharts.com/h-sc/ui

You can probably see why news headlines may not always be new or useful information...