Wednesday, August 4, 2010

WHAT INVESTORS CAN LEARN FROM CHESS - MORNINGSTAR ANALYSIS NO SURPRISE AT ALL

Introduction
This morning Holland's main newspapers reported the results of an investigation by Morningstar, the well-known US-based provider of fund information. And to my surprise the essence of the report was that 2010 has so-far been a difficult year with the bulk of Global Equity funds not being able to beat their most relevant benchmark, the MSCI World.

The MSCI World is a market-value-weighted index combining the largest, most important and liquid listed firms from the World's most developed nations.

We were actually shocked by the level of simplicity of the newspaper analyses. And even more shocked by the fact that we discover articles like this one time and again in almost all international media. And not just that: even within the industry - at the professional level - do this type of 'mistakes' related to black-white thinking strike us.

And black-white thinking provides us with a nce bridge to the game of Chess. And guess what: without often knowing it, top Chess bears quite a few similarities with what is going on here. Well, we can go one step further: chess is one step further than investing!

 What Investors can learn from Chess
The similarities between competitive games

We believe that there are five aspects that can explain why it is often so hard for fund managers to beat benchmarks. They are:

  1. Nature
  2. Behavior
  3. Size
  4. Sector
  5. The Game itself
Let us explain:

Nature
Investment management is like a competition. The combined pool of investors - weighted on the basis of a scheme in which democracy has no meaning but invested money values do - is the enemy. The larger the amount invested by an investor - be it a large institutional investor or a group of private investors - the larger their relative importance within that pool of 'enemies'. The value-weighted combination of investors - through their supply and demand - determine what will happen with the index, in this case the MSCI World.

When comparing the performance of individual investors with the index it is natural and logical to believe that there should be just as many outperformers as underperformers and to assume that their average over- and underperformance records compensate each other neatly. They have to, because in the end the average investor will achieve average results, i.e. index level like returns.

But this is not what we normally see in 'competitive' games! Take chess. The World Chess Federation FIDE did develop a rating system that is based on work by a Hungarian professor, Arpad Elo. If you want to know more about it, click on this Wikipedia Link. Without going in detail we know that all serious chess players in clubs or FIDE tournaments will get such a rating, with updates being calculated every time new results come in. With the system now more than 40 years old, anyone interested in distributions of player quality in competitive games can learn a lot from it. And discussions about the weaknesses of the system within the chess community are at a much higher level than what we often see within the Investment World, where historical return and reputation are still dominating without properly taking 'risk' and 'skill versus luck' into account.


Main conclusion for the purpose of our article: consistently outperforming the 'average' (read 'index' for the purpose of our comparison with Investments) is very difficult. There are far more average and lousy chess players than there are top players. In other words: the distribution of player strengths consists of a small first layer of outperformers, a larger middle zone of people who are 'mediocre' and an even larger zone of 'underperformers'.


And that is what we see back in the Fund Performance vis-a-vis the MSCI World. The bulk of funds is at best mediocre. Something we already knew based on stories about darts-throwing monkeys not really underperforming the index.


Sub-conclusion : It is natural that the group of outperformers is not very big. Outperforming the MSCI World index is not an easy game. And just like in Chess: when games are difficult, continuous outperformance is only possible if you possess 'exceptional' qualities.

But things are even more complicated. The newspaper articles did also state that - when looking at longer or other holding periods - things look even worse. And this corroborates our statement. Actually: the longer the period under study, the smaller the group of consistent outperformers.

Behavior
Investment Funds are basically entities comprised of groups of people that sold a specific strategy to the investing public.So they are the group of 'insiders' chosen to do for the public what the public cannot or does not want to do itself.

And that brings us of course to something of an explanation of why the newspaper articles seem to signal 'big surprise' about the massive underperformance. The Funds were chosen to be insiders. If the bulk of these alleged specialists do not outperform, they should be replaced or at least removed from the industry or from a job within the specific sub-component of the industry if we want to formulate things a bit friendlier. To compare it with the chess world. Suppose we are 'outsiders' who want to sponsor a chess team in a national or international competition. If we want to be champions we hire above-average players that can bring us the title.


We could for instance use the FIDE Rating system to find these players. If they don't deliver, we will not hire them again of course and - through the games they are playing - their rating will drop. The FIDE Rating system will - through this updating process - provide us with a better, i.e. updated, signal on a next occasion. Somehow the investment community has not been capable of creating such a system. Morningstar's star system claims to be that system, but we are not convinced by its results yet.


Instead, most investors use a surrogate rating based on 'historical return' and/or 'reputation' instead. Both are poor predictors of quality in the future.

 Size Matters but is not the whole thing...
How to find the true winners in a complicated competition?


To show that historical return is a bad guiding beacon, we give you the following example. Suppose we 'create' Investment Funds / Strategies by providing different people without any knowledge with a dice. Values of 4, 5 and 6 imply 'buy' and values of 1, 2 and 3 'sell', with the game being buying a call or put option on an underlying index, like the MSCI World.


Now suppose we start with 100 of these 'funds'. If the dice are OK, after one year we are left with some 50 outperforming portfolio managers. In other words: over a shorter period of time a symmetrical distribution of winners and losers is possible.  After two years we are left with 25 outperforming managers. Half of the outperformers over the first year are now back on their humble feet: outperformance in year 1 was followed by underperformance in year 2.


After 3 years we are left with 12 (rounded) outperforming managers. After 4 years 6, after 5 years 3. After 6 years 2 (rounded) and after 7 years, i.e. one complete business cycle, there is one manager that posted outperformance in every year. Seven years in a row! Be sure that this guy shows incredible outperformance with a huge crowd of followers treating him as a fantastic guru.

It is a behavioral thing: people love guru's, want guru's and get them as you can see. Critical analysis of the underlying game is necessary so as to really distinguish 'skill' from 'luck'. Simply looking at the results is not sufficient.


And it gets even more complicated. There is a second behavioral reason why there are not so many winners. And that is related to the fact that there is a second competition going on beneath the surface. And that is a competition in the job market. All those alleged specialists are not just competing with their Funds. They are also competing in the job market, trying to avoid losing their jobs. After all they were hired by their clients to outperform. Now, if I do something totally different than my colleagues it could backfire when I underperform. People will ask me 'You idiot, why did you do that? Couldn't you see that this is a crazy decision?'


However, when I stay close to what others are doing more or less buying and selling the same stocks, I always have an extra layer of defense. Even in those instances where we do underperform as a group. I can always try to get away with remarks like 'Sure. I underperformed. But how could I know. See the competition. No one saw this happening. We all made the same mistakes. This was something no specialist could foresee'.  And I am sure that quite a few of you reading this article will think: 'Isn't that more or less what we heard from decision takers in general after the Global Crisis of 2008/09?'


And THAT is the behavioral game that also helps explain why the bulk is underperforming. When the bulk of funds is underperforming we will find out - when analyzing their holdings - that they are also invested in more or less the same subgroup of securities. If all are buying and selling the same stuff at more or less the same time, we pay too much when we buy and get too little when we sell. Result: underperformance!

Size
In the game of Investing not everything is Chess. One difference is for instance that Funds are selected by groups of smaller investors who combine their resources and select a Fund as portfolio manager to play the investment game on their behalf. This implies 'economies of scale', but that is only the good part of the story. It also implies that those Funds are relatively large and that could automatically translate into an increased focus on stocks that have relatively higher turnover. I.e.: an overweight in large capitalization stocks. And indeed: when analyzing the universe of Investment Funds - independent of Asset Class - we do on average see that they tend to concentrate on relatively larger market caps. This is not just true when looking at all Funds (overweight for large cap Funds vis-a-vis smaller cap Funds), it is even true within size categories.

So this provides us with another explanation of why - at specific moments in time - groups of above-average size might under- or outperform. When markets go through cycles where sometimes large caps do outperform and at other times underperform, we should not be surprised to see skewed distributions of over- and underperformers at any moment in time.

It is actually even worse: larger capitalization stocks are followed by more analysts. They are more well-known firms with also a larger following of financial journalists. Firms that are all but 'neglected'. But Investing is an information game. And now we can go back to our Chess metaphor. The less known a specific type of game plan or opening is, the larger the likelihood that a real Grandmaster will crush the amateur. And that is actually what we see in games between amateurs and Grandmasters: the latter do not play the mainstream variations they are playing against each other, but they often opt for relatively unknown and underanalyzed variations where the difference in skill will do the rest.


So: if Fund managers do - on average - opt for relatively larger capitalizations vis-a-vis their within-category benchmarks just as much as they go - once again on average - for larger capitalization Fund styles, it is an indirect indication that they might not be as much of an insider as they want us to believe.


This is something we see clearly in one of those areas where the best Funds are still outperforming on a structural basis: Emerging and Frontier Markets. 'Winners' in this category do - almost without exception - opt for an overweight of stocks in the lower market cap zones of the MSCI Emerging Markets or they go for an overweight of stocks that are not even part of this index with the 'Losers' showing overweights in those Emerging Markets giant stocks that we all know (Gazprom, Vale, Posco, Reliance, Chinese giants etc).

Sector
When you go for 'larger capitalization' stocks, you automatically also generate sector tilts. Without exception different sectors are represented by different percentages of large firms. The Retail industry is dominated by tons of smaller firms that are therefore relatively underweighted in a large-cap index like the MSCI World. On the other hand: the Financial Services sector - through the essence of its main activities and because of regulatory issues - is overrepresented by relatively large firms and therefore an industry with a strong weight within the MSCI World.

Well, we all know what happened with that sector during the last few years. So no reason to be really surprised that sector-tilts in combination with size-tilts can generate skewed performance distributions!

The Game Itself
The Game itself is important as well. Just like checkers and poker are not the same as chess, global equity management is not the same as emerging market debt. The more complicated the game, and the lower the relative information availability the larger the likelihood that the difference between winners and losers grows.

If there is one group of stocks relatively well analyzed it is the world's largest firms, i.e. the ones in the MSCI World. It is harder not to know a lot about what is going on with those stocks than it is to know quite a bit. The average private investor could create already quite some impressive database for himself by creating a Twitter or RSS feed by simply plugging in the names of the firms in the index. Therefore: the more people know, the more difficult it is to find the gem stone. And also: the more difficult it is - over a period of time - to find that gem stone time and again. Result: Global Equity is a difficult asset class with a relatively large group of struggling service providers and just a small sub-set of outperformers. Just like the Morningstar results were telling us.

Can we still do something with the Chess metaphor here? Yes! 

Chess is a game in which you do not have to capture an offered piece. You have the opportunity to do something else. In checkers you are obliged to capture any piece offered. I.e. less options at your disposal on the average move. Result: you can and need to analyze more moves ahead. This translates into a more complicated game, with a larger percentage of games ending in a draw and a smaller group of 'real outperformers'.

Conclusion
We should not be surprised to see a skewed distribution of Global Equity managers with far more losers than winners. We should be more surprised that people again and again do not seem to understand why this is the case. And we should understand that Investments is a complicated game. A game in which we need to use all tools and analyses at our disposal. 'Reputation' and 'historical return' are nice indicators but they are definitely not sufficient. Databases like Morningstar's or the one of our own partner CAMRADATA are essential tools when trying to find the true outperformers, but be sure: these outperformers do exist! Unfortunately the growing interest in passive management is an indication of growing groups of market participants turning cynical. We hope that our contribution helps you to understand that this is more a token of lousy manager selection than of the bankruptcy of active management. 

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