Value Investing is Predicated on the Efficient Market Hypothesis being Wrong.

Value investing:  there is recurrent mis-pricing of securities

Investors should understand not only what value investing is but also why it is a successful investment philosophy.

At the very core of its success is the recurrent mis-pricing of securities in the marketplace.  

Value investing is, in effect, predicated on the proposition that the efficient-market hypothesis is frequently wrong. 

• If, on the one hand, securities can become undervalued or overvalued, which I believe to be incontrovertibly true, investors will thrive.  
• If, on the other hand, all securities at some future date become fairly and efficiently priced, value investors will have nothing to do.  

It is important, then, to consider whether or not the financial markets are efficient.




The efficient market hypothesis takes three forms.  

• The weak form maintains that past stock prices provide no useful information on the future direction of stock prices.  In other words, technical analysis (analysis of past price fluctuations) cannot help investors.  
• The semi-strong form says that NO published information will help investors to select undervalued securities since the market has already discounted all publicly available information into securities prices.  
• The strong form maintains that there is no information, public or private, that would benefit investors.  

Implication of efficient market hypothesis

Of the three forms of the efficient market hypothesis, I believe that only the weak form is valid.  Technical analysis is indeed a waste of time.

As to the other forms:  yes, the market does tend to incorporate new information into prices - securities prices are neither random nor do they totally ignore available information - yet the market is far from efficient.

The implication of both the semi-strong and strong forms is that fundamental analysis is useless.  Investors might just as well select stocks at random.



Investors applying disciplined analysis can identify inefficiently priced securities and achieve superior returns while taking below-average risks.

There is simply no question that investors applying disciplined analysis can identify inefficiently priced securities, buy and sell accordingly, and achieve superior returns. 

Specifically by finding securities whose prices depart appreciably from underlying value, investors can frequently achieve above-average returns while taking below-average risks. 

The pricing of large-capitalization stocks tends to be more efficient than that of small-capitalization stocks, distressed bonds, and other less-popular investment fare.

While hundreds of investment analysts follow IBM, few, if any, cover thousands of small-capitalization stocks and obscure junk bonds.  Investors are more likely, therefore, to find inefficiently priced securities outside the Standard and Poor's 100 than within it.

Even among the most highly capitalized issues, however, investors are frequently blinded by groupthink, thereby creating pricing inefficiencies.




Efficient-market theory is at odds with the reality of how the financial markets operate.

Is it reasonable to expect that in the future some securities will continue to be significantly mispriced from time to time?

I believe it is.

The elegance of the efficient-market theory is at odds with the reality of how the financial markets operate.




Buffett's "The Superinvestors of Graham and Doddsville"

If the markets were efficient, then how could so many investors, identifiable by Buffett years ago as sharing a common philosophy but having little overlap in their portfolios, all have done so well?

Buffett's "The Superinvestors of Graham and Doddsville" demonstrates how nine value investment disciples of Benjamin Graham, holding varied and independent portfolios, achieved phenomenal investment success over long periods. 

His view is that the only thing the many value investors have in common is a philosophy that dictates the purchase of securities at a discount from underlying value.

 The existence of so many independent successes is so inconsistent with the efficient-market theory.

Genuine News and Noises

Intrinsic value cannot be determined with precision, which makes it hard to prove that stock prices deviate from intrinsic value.


An important principle at the heart of the Efficient Market Hypothesis is the law of one price.  The law asserts that in an efficient market, the same asset cannot simultaneously sell for two different prices.  If that happened, there would be an immediate arbitrage opportunity, meaning a way to make a series of trades that are guaranteed to generate a profit at no risk.


News and Noises

The only thing that makes an investor  change his mind about an investment is genuine news.

But humans might react to something that does not qualify as news, such as seeing an ad for the company behind the investment that makes them laugh.  In other words, there are many who make decisions based on noises rather than actual news.  These are called "noise traders".  They trade on noise as if it were information.  "THERE ARE IDIOTS.  Look around."

Picking the best stocks is like picking out the prettiest faces in a beauty contest.

Keynes wrote:  "Day to day fluctuations in the profits of existing investments, which are obviously of an ephemeral and non-significant character, tend to have an altogether excessive, and even an absurd, influence on the market."

Keynes was also sceptical that professional money managers would serve the role of the "smart money" that Efficient Market Hypothesis defenders rely upon to keep markets efficient.  Rather, he thought that the pros were more likely to ride a wave of irrational exuberance than to fight it.  One reason is that it is risky to be a contrarian.  "Worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally."



Keynes's beauty contest analogy

This is still an apt description of what money managers try to do.

Many investors call themselves "value managers," meaning they try to buy stocks that are cheap.

Others call themselves "growth managers," meaning they try to buy stocks that will grow quickly.

But of course no one is seeking to buy stocks that are expensive, or stocks of companies that will shrink.

So what are all these managers really trying to do?

They are trying to buy stocks that will go up in value - or , in other words, stocks that they think OTHER investors will LATER decide should be worth more. 

And these other investors, in turn, are making their own bets on others' FUTURE valuations.

Buying a stock that the market does not fully appreciate today is fine, as long as the rest of the market comes around to your point of view sooner than later!

Costs of trading, illiquid markets and costs associated with gathering and analyzing information affect security prices.

Two securities that should trade for the exact same price in an efficient market may trade at different prices for various reasons:

1. If the costs of trading on the mispricing (to make a profit) for the lower cost traders are greater than the potential profit.
2. In such cases, these prices are still "efficient" within the bounds of arbitrage.  The bounds of arbitrage are relatively narrow in highly liquid markets (e.g., U.S. T-bills), but wider in relatively illiquid markets.
3. There are always costs associated with gathering and analyzing information.  Net of information acquisition costs, the return offered on a security should be commensurate with the security's level of risk.  If superior returns can be earned after deducting information-acquisition costs, the market is relatively inefficient.

Factors Contributing to and Impeding a Market's Efficiency

Market participants:   

The greater the number of active market participants (investors and financial analysis) that analyze an asset or security, the greater the degree of efficiency in the market.

Information availability and financial disclosure:

The availability of accurate and timely information regarding trading activities and traded companies contributes to market efficiency.

Limits to trading:

The activities of arbitrageurs, who seek opportunities to trade on mispricings in the market to earn arbitrage (riskless) profits, contribute to market efficiency.

Transactions costs and information acquisition costs:

Investors should consider transaction costs and information-acquisition costs in evaluating the efficiency of a market.

Market Value versus Intrinsic Value

Market Value

The market value or market price of the asset is the price at which the asset can currently be bought or sold.  

It is determined by the interaction of demand and supply for the security in the market.


Intrinsic Value

Intrinsic value or fundamental value is the value of the asset that reflects all its investment characteristics accurately.

Intrinsic values are estimated in light of all the available information regarding the asset; they are not known for certain



Efficient Market

In an efficient market, investors widely believe that the market price reflects a security's intrinsic value.


Inefficient Market

On the other hand, in an inefficient market, investors may try to develop their own estimates of intrinsic value in order to profit from any mispricing (difference between the market price and intrinsic value).

Efficient Market versus Inefficient Market

An information efficient market (an efficient market) is one where security prices adjust rapidly to reflect any new information.

It is a market where asset prices reflect all past and present information.

Investment managers and analysts are interested in market efficiency because it dictates how many profitable trading opportunities may abound in the market.



Efficient market

In an efficient market, it is difficult to find inaccurately priced securities.  

Therefore, superior risk-adjusted returns cannot be attained in an efficient market.

It would be wise to pursue a passive investment strategy which entails lower costs.

In an efficient market, the time frame required for security prices to reflect any new information is very short.   

Further, prices only adjust to new or unexpected information (surprises).



Inefficient market

In an inefficient market, securities may be mispriced.

Trading in these securities can offer positive risk-adjusted returns. 

In such a market, an active investment strategy may outperform a passive strategy on a risk-adjusted basis.

Fundamental Analysis Advocates versus Efficient Market Advocates

Fundamental Analysis Advocates

The concept of security analysis in general, and fundamental analysis in particular, is based on the assumption that at least some investors are capable of identifying stocks whose intrinsic values differ from their market values.

Fundamental analysis operates on the broad premise that some securities may be mispriced in the marketplace at least some of the time.

Fundamental analysis may be a worthwhile and profitable pursuit:

• if securities are occasionally mispriced, and 
• if investors can identify mispriced securities.

To many, those two premises seem reasonable.



Efficient Market Advocates

However, there are others who do not accept the assumptions of fundamental analysis.

These so-called efficient market advocates believe

• that the market is so efficient in processing new information that securities trade very close to or at their correct values at all times. and 
• that even when securities are mispriced, it is nearly impossible for investors to determine which stocks are overvalued and which are undervalued.

Thus, they argue, it is virtually impossible to consistently outperform the market.

In its strongest form, the efficient market hypothesis asserts the following:

1.  Securities are rarely, if ever, substantially mispriced in the marketplace.
2.  No security analysis, however detailed, is capable of identifying mispriced securities with a frequency greater than that which might be expected by random chance alone.

A Random Walk Down Wall Street - Part Three 3: The New Investment Technology

Chapter 11. Potshots at the Efficient-Market Theory and Why they Miss

Robert Shiller concluded from a longer history of stock market fluctuations that stock prices show far “too much variability” to be explained by an efficient-market theory of pricing and that one must look to behavioral considerations and to crowd psychology to explain the actual process of price determination in the stock market.

The author reviewed all the recent research proclaiming the demise of the efficient-market theory and purporting to show that market prices are, in fact, predictable. His conclusion is that such obituaries are greatly exaggerated and that the extent to which the stock market is usefully predictable has been vastly overstated. He shows that following the tenets of the efficient-market theory – that is, buying and holding a broad-based market index fund – is still the only game in town. Although market may not always be rational in the short run, it always is over the long haul.



I. What do we mean by saying markets are efficient?

1. Markets can be efficient even if they sometimes make egregious errors in valuation. Markets can be efficient even if stock prices exhibit greater volatility than can apparently be explained by fundamentals such as earnings and dividends.

2. Economists view markets as amazingly successful devices for reflecting new info rapidly and, for the most part, accurately. Above all, we believe that financial markets are efficient because they don’t allow investors to earn above average returns without accepting above-average risks.

3. No one can consistently predict either the direction of the stock market or the relative attractiveness of individual stocks and thus no one can consistently obtain better overall returns than the market. And while there are undoubtedly profitable trading opportunities that occasionally appear, there are quickly wiped out once they become known. No one person or institution has yet to produce a long-term, consistent record of finding money-making, risk-adjusted individual stock-trading opportunities, particularly if they pay taxes and incur transactions costs.




II. Potshots that completely miss the target

1. Dogs of the Dow: out-of-favor stocks eventually tend to reverse direction. The strategy entailed buying each year the ten stocks in the DJ that had the highest dividend yields. The idea was that these ten stocks were the most out of favor, so they typically had low price-earnings multiples and low price-to-book-value
ratios as well. This strategy consistently underperformed the overall market during the last half of the 1990s. “The strategy became too popular” and ultimately self-destructed.

2. January Effect: stock-market returns have tended to be especially high during the first two weeks of January. The effect appears to be particularly strong for smaller firms. One possible explanation for it is that tax effects are at work. Some investors may sell securities at the end of the calendar year to establish
short-term capital losses for income tax purposes. Although this effect could be applicable for all stocks. It would be larger for small firms because stocks of small companies are more volatile and less likely to be in the portfolios of taxexempt institutional investors and pension funds. However, the transaction costs of trading in the stocks of small companies are substantially higher than for larger companies (because of the higher bid-asked spreads) and there appears to be no way a commission-paying ordinary investor could exploit this anomaly.

3. Hot news response: some academics believe that stock prices underreact to news events and, therefore, purchasing (selling) stocks where good (bad) news comes out will produce abnormal returns. Fama found that apparent underreaction to info is about as common as overreaction, and post-event continuation of abnormal returns is as frequent as post-event reversal.

4. It is obvious that any truly repetitive and exploitable pattern that can be discovered in the stock market and can be arbitraged away will self-destruct. Indeed, the January effect became undependable after it received considerable publicity.



III. Potshots that get close but still miss the target

1. Short-term momentum: Lo and Mackinlay found that for two decades broad portfolio stock returns for weekly and monthly holding periods showed positive serial correlation. Moreover, Lo and others have suggested that some of the stock-price pattern used by so-called technical analysis may actually have some
modest predictive power. Behavioral economists find such short-run momentum to be consistent with psychological feedback mechanisms. Individuals see a stock price rising and are drawn into the market in a kind of “bandwagon effect.”
However, two factors prevent us from believing markets are inefficient:
a. It is important to distinguish statistical significance from economic significance. The statistical dependencies giving rise to momentum, in fact, are extremely small and are not likely to permit investors to realize excess returns.
b. We should ask whether such patterns of serial correlation are consistent over time.

2. The dividend jackpot approach: Depending on the forecast horizon involved, as much as 40% of the variability in future market returns can be predicted on the basis of the initial dividend yield of the market as a whole. Investors have earned higher total rates of return from the stock market when the initial dividend yield of the market portfolio was relatively high. These findings are not necessarily inconsistent with efficiency. Dividend yields of stocks tend to be high (low) when interest rates are high (low). Consequently, the ability of initial yields to predict returns may simply reflect the adjustment of the stock market to general economic conditions. Moreover, the dividend behavior of US corporations may have changed over time. Companies in 21st century may be more likely to institute a share repurchase program rather than increase their dividends. Thus dividend yield may not be as meaningful as in the past. Finally, this phenomenon does not work consistently with individual stocks. Investors who simply purchase a portfolio of individual stocks with the highest dividend yields in the market will not earn a particularly high rate of return.

3. The Initial P/E predictor: Campbell and Shiller report that over 40% of the variability in long-horizon returns can be predicted on the basis of the initial market P/E.

4. Long-run return reversals: buying stocks that performed poorly during the past three years or so is likely to give you above-average returns over the next three years. However, return reversals over different time periods are often rooted in solid economic facts rather than psychological swings. The volatility of interest rates constitutes a prime economic influence on share prices. Because bonds – the front-line reflectors of interest-rate direction – compete with stocks for the investor’s dollars, one should logically expect systematic relationships between interest rates and stock prices. When interest rates go up, share prices should fall, other things being the same, so as to provide larger expected stock returns in the future. Only if this happens will stocks be competitive with higher yielding bonds. Similarly, when interest rates fall, stocks should tend to rise because they can promise a lower total return and still be competitive with lower yielding bonds.

5. The small firm effect: since 1926, small firms have produced returns over 1.5% points larger than the returns from large stocks. But, small stocks may be riskier than larger stocks and deserve to give investors a higher rate of return. Thus, even if this effect was to persist in the future, it’s not at all clear that such a finding would violate market efficiency. Moreover, this effect may due to “survivorship bias”. And in most world markets it was the larger cap stocks that produced larger rates of return.



IV. Why even close shots miss

1. Regarding to internet bubble, when we know ex post that major errors were made, there were certainly no clear ex ante arbitrage opportunities available to rational investors. And even when clear mispricing arbitrage opportunities seem to have existed, there was no way to exploit them.

2. To me, the most direct and most convincing tests of market efficiency are direct tests of the ability of professional fund managers to outperform the market as a whole. But the fact is that professional investment managers are not able to outperform index funds that simply buy and hold the broad stock-market portfolio. During the past 30 years, about two-thirds of the funds proved inferior to the market as a whole. The same result also holds for professional pension fund managers. There are some funds which beat index. But the problem for investors is that at the beginning of any period they can’t be sure which funds will be successful and survive.



V. A Summing Up

1. Market valuation rest on both logical and psychological factors.

2. Stock prices display a remarkable degree of efficiency. Info contained in past prices or any publicly available fundamental info is rapidly assimilated into market prices. Prices adjust so well to reflect all-important info that a randomly selected and passively managed portfolio of stocks performs as well as or better than the portfolios selected by the experts.

3. With respect to the evidence indicating that future returns are, in fact, somewhat predictable, there are several points to make.
a. There are considerable questions regarding the long-run dependability of these effects. Many could be the result of “data snooping”.
b. Even if there is a dependable predictable relationship, it may not be exploitable by investors (e.g. high transaction costs).



A Random Walk Down Wall Street - The Get Rich Slowly but Surely Book Burton G. Malkiel
http://people.brandeis.edu/~yanzp/Study%20Notes/A%20Random%20Walk%20down%20Wall%20Street.pdf

Why Value Investing works. Buying cheaply works.

WHY VALUE INVESTING WORKS

Markets are not Efficient
All you should worry about since you aren’t going to be able to outguess the market is minimizing transaction costs, and allocating assets that creates an appropriate risk profile. What I think you ought to know about that is two things.

• The first is that there is overwhelming statistical evidence that markets are not efficient. In all countries and all periods of time since the early 20th century, that there are variables that can be reliably used to outperform the market and that clearly contradicts the premise that nobody can outperform the market. 
• There is a sense in which absolutely and fundamentally markets are efficient and it is this—that when we buy as night follows the day someone else is selling that stock thinking it is going down--and one of you is always wrong. (Don’t play the patsy!)

Why Are You on the Right Side of the Trade?
Another way of saying that is not everybody can outperform the market. The famous humorist called Garrison Keiller talks about a fictional town called Lake Woebegone. In Lake Woebegone all the women are beautiful, all the men are tall and all the children are above average. In this game all the children are average on average which means half of them underperforms the market. So when you start to think about investing, you must be able to answer the question:

• Why are you able to beon the right side of the particular trade? 
• Why are you the one who is right, and the person who is trading with you is wrong? That is the most fundamental aspect of Investing. 
• Where and what is your investing edge? 
• What puts you on the right side of the trade?

Buying Cheaply Works
When we talk about value investing there is a lot of evidence that value investors have been on the
right side of the trade. 

• The statistical studies that run against or contradict market efficiency almost all of them show that cheap portfolios—low market-to-book, low price-to-book—outperform the markets by significant amounts in all periods in all countries—that is a statistical, historical basis for believing that this is one of the approaches where people are predominantly on the right side of the trade.  And, of course, someone else has to be on the wrong side of the trade.
• Those studies were first done in the early 1930s; they were done again in the early 1950s. And the ones done in the 1990s got all the attention because the academics caught on. There is statistical evidence that the value approaches—buy cheap securities—have historically outperformed the market.  Buying Cheap works.

http://csinvesting.org/wp-content/uploads/2012/06/greenwald-vi-process-foundation_final.pdf

Jeremy Siegel - Efficient Market Theory and the Recent Financial Crisis

If some degree of mis-pricing exists in the stock market, it does not persist for long.

Market valuations rest on both logical and psychological factors.

The theory of valuation depends on the projection of a long-term stream of dividends whose growth rate is extraordinarily difficult to estimate.  Thus, fundamental value is never a definite number.  It is a fuzzy band of possible values, and prices can move sharply within this band whenever there is increased uncertainty or confusion.  Moreover, the appropriate risk premiums for common equities are changeable and far from obvious either to investors or to financial economists.  Thus, there is room for the hopes, fears, and favorite fashions of market participants to play a role in the valuation process.  

History provides extraordinary examples of markets in which psychology seemed to dominate the pricing process, as in the tulip-bulb mania in seventeenth century Holland and the Internet bubble at the turn of the twenty-first century.  It is doubtful that the current array of market prices ALWAYS represents the best estimate available of appropriate discounted value.

Nevertheless, the evidence suggest that stock prices display a remarkable degree of efficiency.  Prices adjust so well to important information.  Information contained in past prices or any publicly available fundamental information is rapidly assimilated into market prices.  If some degree of mis-pricing exists, it does not persist for long.

"True value will always out" in the stock market.  To paraphrase Benjamin Graham, ultimately the market is a weighing mechanism, not a voting mechanism.  

Efficient Market Hypothesis: Fact Or Fiction? "Efficient" refers to informational efficiency only.

The efficient markets hypothesis (EMH) in all of its forms, whether strong, semi-strong, or weak, is normative, not positive, i.e., it is an assertion about the way markets should behave in an ideal, utopian world, not a statement about the way markets actually do work in the real, practical world. Simple observation shows that the EMH in all its forms is fallacious. Both Kindleberger and Mackay give historical examples of stock market irrationality and inefficiency.

The efficient markets hypothesis may have advanced many academic careers, but it has not demonstrably increased the wealth of any investor over what would have been created otherwise. The EMH and the related capital asset pricing model, as opposed to the operating enterprise valuation model, may be useful as a standard of market perfection in studies of the market as a whole, but not in the valuation or selection of common stocks for investment.

The term "efficient" in the efficient markets hypothesis refers to informational efficiency only. It does not include mechanical operational efficiency or necessarily societal welfare efficiency.

The EMH explicitly assumes that all market participants have access to the same information in either a strong, semi-strong, or weak sense of the hypothesis.

• This simplifying assumption is chosen because it is necessary for mathematical tractability and thus highly convenient. 
• What makes this assumption unacceptably implausible is the meaning of the term "information" which is often overlooked. 
• Data is not information. Rather, information is data that has been processed and interpreted with judgment based on intelligence, knowledge and experience. 
• Does anyone believe that all market participants are endowed equally, not with access to data, but with the same intelligence, knowledge and experience? 

Competitive, properly-regulated markets may approach the semblance of "data efficiency" in the relative sense of eliminating arbitrage opportunities subject to trading costs and taxes, but no market is efficient in any absolute sense of equating price at all times to intrinsic economic value. This margin between value and price is the major key to successful value investing.

Buffett: What students should be learning is how to value a business.

John Kenneth Galbraith once slyly observed that economists were most economical with ideas: They made the ones learned in graduate school last a lifetime. University finance departments often behave similarly. Witness the tenacity with which almost all clung to the theory of efficient markets throughout the 1970s and 1980s, dismissively calling powerful facts that refuted it “anomalies.” (I always love explanations of that kind: The Flat Earth Society probably views a ship’s circling of the globe as an annoying, but inconsequential, anomaly.)

Academics’ current practice of teaching Black-Scholes as revealed truth needs re-examination. For that matter, so does the academic’s inclination to dwell on the valuation of options. You can be highly successful as an investor without having the slightest ability to value an option. What students should be learning is how to value a business. That’s what investing is all about.

http://www.berkshirehathaway.com/letters/2010ltr.pdf

Risk and Return - Find Investments offering High Returns with Low Risk

A positive correlation between risk and return would hold consistently only in an efficient market.  Any disparities would be immediately corrected, this is what would make the market efficient.

In inefficient markets it is possible to find investments offering high returns with low risk.  These arise 

• when information is not widely available, 
• when an investment is particularly complicated to analyze, or 
• when investors buy and sell for reasons unrelated to value.  

It is also common place to discover high-risk investments offering low returns.  Overpriced and therefore risky investments are often available

• because the financial markets are biased toward overvaluation and 
• because it is difficult for market forces to correct an overvalued condition if enough speculators persist in overpaying.  
• Also, unscrupulous operators will always make overpriced investments available to anyone willing to buy, they are not legally required to sell at a fair price.

Since the financial markets are inefficient a good deal of the time, investors cannot simply select a level of risk and be confident that it will be reflected in the accompanying returns.  Risk and return must instead be assessed independently for every investment.  

In point of fact, greater risk does not guarantee greater return.  To the contrary, risk erodes return by causing losses.

It is only when investors shun high-risk investments, thereby depressing their prices, that an incremental return can be earned which more than fully compensates for the risk incurred.

By itself risk does not create incremental return; only price can accomplish that.

Efficient Market Hypothesis: Fact Or Fiction?

Published in Investing on 5 January 2012

Our economics series looks at the question of whether we really can beat the market.

How many times have you heard a would-be private investor saying something like: "You can't beat the game, because the big institutions always get the information ahead of you and get in first"?

If you believe that, you might be a proponent of the Efficient Market Hypothesis, which says that because the financial world is efficient in terms of information, it is impossible to consistently beat the market based on what you know when you choose where to put your money.

The idea was first developed by the economist Eugene Fama in the 1960s, following on from his observations that the day-to-day movements of the stock market resemble a random walk as much as anything else. And for a while, it came to be pretty much accepted as fact.

On the face of it, it does seem reasonable. Given that everyone has access to the same information, and there is a truly free price-setting equilibrium in which the balance of supply and demand is the determining factor in setting share prices (as it pretty much is with any free-traded commodity), surely the price will reflect all of the information available at the time, and you can't beat the market.

Fine in the short term

In the short term, the idea seems pretty much spot-on. New results are released and they look good, and you try to get in 'ahead of the market' to profit from them? Well, no matter how quick you are, it's too late and the price has already jumped. That's really no surprise, because the sellers of the shares have the same new information too, and the equilibrium point between supply and demand will instantly change.

But in the longer term, the Efficient Market Hypothesis is widely considered to be flawed. In fact, if you believed it held true over serious investing timescales, you probably wouldn't be reading this -- you'd have all your investing cash in a tracker fund and you'd be spending your spare time doing something else. (And that's actually not a bad idea at all, but it's perhaps something for another day).

There is plenty of empirical evidence that the market is what Paul Samuelson described as "micro-efficient" but "macro-inefficient", such that it holds true for individual prices over the short term but fails to explain longer-term whole-market movements.

Long term? Hmm!

And there are others, including the noted contrarian investor David Dreman, who argue that this "micro efficiency" is no efficiency at all, claiming instead that short-term response to news is not what investors should be interested in, but the longer-term picture for a company. It's pretty clear which side of that argument Foolish investors will come down on.

So why doesn't it work in the long run, and how is it possible to beat the market even in the presence of the ubiquity of news and an instantly adjusting price mechanism? Well, the major flaw is that the theory assumes that all participants in the market will act rationally, and that the price of a share will always reflect a truly objective assessment of its real value. Or at least that the balance of opinion at any one time will even out to provide an aggregate rational valuation.

It doesn't take a trained economist to realise what nonsense that can be. Any armchair observer who watched supposedly rational investors push internet shares up to insane valuations during the tech share boom around the year 2000 saw just how the madness of crowds can easily overcome calm rationality.

And the same is true of the recent credit crunch, when panicking investors climbed aboard the 'sell, sell, sell' bandwagon, pushing prices for many a good company down to seriously undervalued levels. What happens is that human emotion just about always outstrips rationality -- good things are seen as much better than they really are, and bad things much worse.

Irrational expectations

And it's not just these periods of insanity, either. There is, for example, strong evidence that shares with a low price-to-earnings ratio, low price-to-cash-flow ratio and so on, tend to outperform the market in the long run. And high-expectation growth shares are regularly afforded irrationally high valuations, and end up reverting to the norm and failing to outperform in the long term.

So what does that all say about the Efficient Market Hypothesis? Well, it certainly contributes to understanding how markets work, but we also need to include emotion, cognitive bias, short-term horizons and all sorts of other human failings in the overall equation.

And that means we can beat the market average in the long term, if we stick to objective valuation measures, don't let short-term excitements and panics sway us, and rein in our usual human over-optimism and over-pessimism.

http://www.fool.co.uk/news/investing/2012/01/05/efficient-market-hypothesis-fact-or-fiction.aspx

A brief history of behavioural finance

by THE INVESTOR on JULY 27, 2010

Behavioural finance has moved into the mainstream. In this guest post, Tim fromThe Psy-Fi Blog gets us up to speed.

Noble Prize winning committees aren’t renowned for consistency. Giving Barack Obama the Peace Prize for not being George W. Bush is a triumph of hope, but hardly based on rational analysis.

We might also wonder if the selection panel got its wires crossed when it awarded the Economics prize to a psychologist.

But it wasn’t just any old shrink who got the bauble. It was Daniel Kahneman, half of the dynamic duo that invented the whole topic of behavioural finance.

The other half, Amos Tversky, died in 1996. Between them, Tversky and Kahneman pump primed a change in the way we expect stocks to behave.

Outside credit rating agencies, it’s no longer enough to assume we can predict market movements on the basis of number crunching on a grand scale.

Now we need to take our own mental confusion into account.

A simple observation that changes everything

The revolution began when Daniel Kahneman noticed how explanations of changes in task performance were based on a mental model that had little to do with actual behaviour.

Airforce flight instructors believed that praising students after a good flight and criticising them after a bad one led to worse performance in the first case and better in the second. But Kahneman theorised that this was simply mean regression in action – that regardless of what the instructors said or did, a poor performance was likely to be followed by a better one and a good performance by a worse one.

This observation kicked off a whole range of discoveries, with ramifications that investors cannot afford to ignore.

In particular, that mean regression might be the underlying principle behind stock movements is an idea that’s been around for over a century – but it hasn’t prevented billions of pounds being made by analysts, gurus, tipsheets, advisers and the whole panoply of apparently omniscient soothsayers that inhabit the securities industry and charge for saying otherwise.

Tversky and Kahneman’s big idea means that this is all an utterly pointless waste of money. Most short-term market movements are simple mean regression in action. It’s only human mental confusion that attributes these random movements to some kind of underlying purpose.

You don’t think like you think you think

As they dug through a series of remarkable experiments, Tversky and Kahneman began to uncover a previously unresearched series of behavioural biases – strange twists in human nature that cause us to act irrationally and against our own interests.

In Judgement Under Uncertainty (1973) they outlined a series of these behaviours. In doing so, they gave birth to behavioural finance.

In essence what they showed was that people don’t act rationally, as defined by correctly calculating the probabilities of events, especially rare ones.

Now you may not think that surprising. After all, we don’t spend our days carefully calculating risks and rewards.

Yet this was exactly the dominant approach of economics at the time – the so-called Efficient Markets Hypothesis, which argues that all information about a stock at any given time is embedded in a single value, the price.

Instead, Kahnemann and Tversky showed that there are regular patterns of irrationality that lie behind people’s behaviour:

• We judge people based on stereotypes.

• We assess the likelihood of events happening based on our ability to retrieve from memory similar events.

• We tend to make decisions based on some arbitrary starting point.

Labeled in turn the representative heuristic, the availability bias andanchoring, these three behaviours do a pretty good job of derailing our attempts to rationalise about investments.

Next came Prospect Theory (1979) – the first attempt at an explanation for the strange asymmetric risk taking behaviour they’d observed.

As other researchers followed up on this research, a whole raft of added behavioural twitches came to light. We are, quite simply, a mass of contradictory and illogical behaviours, to the point where it’s a wonder we can get out of bed in the morning, let alone be trusted with a kettle and a gas hob.

In light of these discoveries, it’s not surprising that most people are advised toabandon attempts to pick individual stocks and simply buy the market via an index tracker instead.

Could behavioural finance be wrong, too?

But there’s another twist in the history of behavioural finance, which is that the uncovering of this unsuspected mental world of confusion has begun to bother some researchers.

They agree that we’re essentially highly-evolved apes with an instinct for survival honed in a very different environment. But they wonder how it’s possible to reconcile the contradictions discovered by psychologists in a way that means we can function at all.

The answer, it seems, is that behavioural finance may also be wrong, although in some very peculiar ways.

Their evidence comes from taking experiments out of the laboratory and into the real world, and also by trying to explain human behaviour using an integrated theory of mental processing that doesn’t look anything like the statistical analyses so beloved of financial researchers.

The economist John List, for example, has been described as the most hated man in economics, largely on account of how his real-world experiments have unpicked a range of the most cherished theories in finance.

List has shown that outside the laboratory people aren’t altruistic in the way they are inside it, and that loss aversion – the idea that people are symmetrically inclined to avoid taking a loss but happy to take a profit based on some arbitrary purchasing anchor point – is not a general psychological principle.

List’s main point that if you put people in a lab experiment they’ll behave the way you expect them to, not the way they’d do naturally (whatever that may be).

You don’t think like they thought you think, either

A second front on behavioural finance has opened up around the way that we actually process information.

Although behavioural finance is superficially very different from the old Efficient Markets approach, underlying it is a similar model of the way that we make decisions, suggesting we perform abstract statistical calculations. Behavioural finance says it’s just that in the behavioural models we get the answers wrong.

But some researchers are now arguing this is a mistaken view of the human brain, and that we do something much simpler, which yields similar results, using an idea known as satisficing.

Satisficing is simply an approach that means we take the best answer we can come up with, given the range of information we have available to us.

Bizarrely the satisficing theories suggests that while a certain amount of information about a certain topic will lead us to improved solutions, beyond this point our decision making accuracy goes down!

If true, it again means there’s a limit to the effectiveness of stock analysis – although that’s still no excuse for simply sticking pins into the price pages of theFinancial Times.

Get your head examined

Scientific advance happens one funeral at a time, and resistance to the suggestion that behavioural finance is flawed is fierce. Progress happens only when someone finds a big enough pair of boots to kick down the old barriers.

That’s what Kahneman and Tversky started back in the 1970s, and the former’s Nobel Prize is unlikely to be the last time a psychologist wins the Economics prize.

Investors, meanwhile, should avoid wasting their money on hopeless explanations of future market movements. And if they can’t, perhaps they should go see a shrink instead?

Read more of Tim’s musings over on his Psy-Fi blog.

http://monevator.com/2010/07/27/behavioural-finance/

Defenders of the Efficient Market Hypothesis

Buffett debunked the Efficient Market Hypothesis: The Superinvestors of Graham-and-Doddsville

Paul the octopus proves Buffett was right
GREG HOFFMAN
July 14, 2010 - 12:08PM

The unlikely hero of the recent World Cup of football? Paul the octopus, a common cephalopod living in a tank at a Sea Life Centre in Oberhausen, Germany.

In case you missed Paul’s highly-publicised predictions, he correctly forecast the winner of all seven of Germany’s World Cup games and the winner of the final. Paul became a media sensation, although he wasn't much use in interviews.

The idea that an octopus would even know of the World Cup, let alone be able to forecast its outcome, is of course ridiculous. Paul can tell us nothing useful about football. But our collective fascination with a Nostradamus octopus is reminiscent of a parable told by the world’s greatest investor more than 25 years ago.

In 1984 Warren Buffett penned an article titled The Superinvestors of Graham-and-Doddsville, based on a speech he had given on the occasion of the 50th anniversary of his mentor Ben Graham’s legendary textbook, Security Analysis.

In it, Buffett rejected the then growing (and now entrenched) view in academia that markets are ''efficient'' because ''stock prices reflect everything that is known about a company’s prospects and about the state of the economy.''

Many academics conclude that anyone who beats the market (like Buffett) is simply lucky; an argument to which Buffett presents a devastating rebuttal.

He asks the reader to ''imagine a national coin-flipping contest'' where 225 million Americans wager a dollar and flip a coin each morning. Each makes their call before flipping and the winners double their stake by taking the money from the losers (who drop out).

''After ten flips on ten mornings, there will be approximately 220,000 people in the United States who have correctly called ten flips in a row. They each will have won a little over $1,000.''

After 20 days, 215 people would have successfully called their coin flips 20 times in a row and each be sitting on $1m in winnings. He suggests that such people would, by this stage, probably start writing books about their success and ''and tackling skeptical professors with, ‘If it can’t be done, why are there 215 of us?’'' Some might even crawl into a fish tank and start predicting the outcomes of sporting contests.

But, as Buffett points out, exactly the same result would be achieved if 225 million orangutans (or octopi) had engaged in the same activity.

Having set the stage for scepticism with his coin-flipping parable, Buffett makes a pre-emptive strike against it; ''I would argue that there are some important differences in the examples I am going to present. For one thing, if (a) you had taken 225 million orangutans distributed roughly as the U.S. population is; (b) 215 winners were left after 20 days; and if (c) you found that 40 came from a particular zoo in Omaha, you would be pretty sure you were on to something.''

Buffett says that if you find an unusual concentration of abnormal results in some kind of geographic area (be it successful coin-flipping orangutans or the incidence of cancer, for instance), it calls for further investigation.

''In addition to geographical origins,'' writes Buffett, ''there can be what I call an intellectual origin.'' He then puts his view that an unusually high number of successful ''coin flippers'' in the investment world employ a similar philosophy; value investing.

After cataloguing the track records of various successful investors who he had pre-identified, Buffett sums up there approach thusly; ''...these investors are, mentally, always buying the business, not buying the stock ... all exploit the difference between the market price of a business and its intrinsic value.''

It’s astounding to me that this approach isn’t more widely followed. Think of the five most respected names in the Australian funds management industry (as opposed to the biggest names). I bet that of the names that spring to mind for most people, at least two would have a strong value investing flavour to their approach.

Those names might include Platinum Asset Management, Perpetual, Maple-Brown Abbott and Argo Investments. Other approaches are likely to be top of the pops in any single year but, over the full sharemarket cycle, you’re likely to find a cluster of value investors near the top of the long term performance league table.

It doesn’t take the predictive powers of a German octopus to conclude that the same will prove true by the time we’re through with this current cycle.

Conventional economic theory tells us that people like Kerr Neilson and Warren Buffett are statistical flukes. But, unlike Paul the octopus, their stock selections are based on a pre-defined philosophy. That should tell us something about the efficient market hypothesis (it's flawed) and the type of approach—the intellectual origin—these successful investors employ (it's successful).

This article contains general investment advice only (under AFSL 282288).

Greg Hoffman is research director of The Intelligent Investor. BusinessDay readers can enjoy a free trial offer at The Intelligent Investor website. For more Intelligent Investor articles click here..

Chuck out your CAPM and burst your beta, the truly chic academics are now seeking to explain why value stocks outperform.

The business schools reward difficult complex behaviour more than simple behaviour, but simple behaviour is more effective. - Warren Buffett

The Efficient Market Hypothesis (EMH) and Modern Portfolio Theory (MPT) are based on a simple assumption that risk is defined by volatility. According to the theory, investors are risk adverse: they are willing to accept more risk (volatility) for higher payoffs and will accept lower returns for a less volatile investment. The theory is simple and elegant, and can lead further into ingenuous mathematical proofs and equations, which probably has a lot to do with why it has become so widely accepted.

When Markowitz and Sharpe et al needed a definition of risk, they chose to define risk as volatility, the greater the volatility of the portfolio, measured either in terms of standard deviation or beta, the greater the risk.

How did these researchers know that volatility was a good measure of risk? They didn't, nor did they do any research to find out. The observation was made that the share market, which is generally thought to be more risky than cash investments, had the highest volatility. The principle was adopted generally without further evidence that volatility was a good way to measure risk.

Economists find this definition of risk compelling, because it is based on an assumption that makes perfect logical sense, that investors should be risk adverse, and that in today's well informed, sophisticated markets everyone acts perfectly rationally and takes no risk that is not justified by a bounty of evidence in support.

But the question is still there, why this measure of risk rather than securities analysis as espoused by Graham and Dodd, examining the virtues of each company by a good look at their financial strength, earnings, debt, sales success or many other measures that management use?

One doesn't have to get too far in examining the theory to find big gaps in the logic. Investors are very concerned by downside volatility, but how many object when their portfolio moves up? Volatility is a measure that regards upside movement as equally bad as movement to the downside. What about inflation and the terrible toll it extracts on non-growth assets? Finally, speculative stocks which are extremely volatile do not fit into this mold as they certainly do not give superior returns, as a diversified group or otherwise. Right from the start this definition of risk seemed unrealistic.

Unrealistic or not, an entire generation of investors has grown up with the idea that volatility is risk. Services that rate managed funds examine volatility as a central concern, and "risk adjusted" historic returns are frequently a major factor in determining how many stars a manager is given by the rating services.

There are many problems with the whole concept. For starters there actually isn't any permanent correlation between risk (when defined as volatility) and return. High volatility does not give better results, nor does lower volatility give lesser results.

In 1977, over a decade before Markowitz and Sharpe received their Nobel Prizes for their work on portfolio theory, a paper appeared reviewing the research on risk (J. Michael Murphy, "Efficient Markets, Index Funds, Illusion, and Reality", Journal of Portfolio Management (Fall 1977), pp. 5-20.). Some of the conclusions were startling, at least for EMH believers. Murphy cited four studies that found "realised returns appear to be higher than expected low low-risk securities and lower than expected for high-risk securities ... or that the [risk-reward] relationship was far weaker than expected." The author continued on: "Other important studies have concluded that there is not necessarily any stable relationship between risk and return; that there often may be virtually no relationship between return achieved and risk taken; and that high volatility unit trusts were not compensated by greater returns". (Italics original)

Another paper (Haugen and Heins, "Risk and the Rate of Return on Financial Assets: Some Old Wine in New Bottles," Journal of Financial and Quantitative Analysis (December 1975), pp 775-84) concluded: "The results of our empirical effort do not support the conventional hypothesis that risk - systematic or otherwise - generates a special reward." These papers were published in the mid to late 70s, just as EMH and MPT were really taking off and "revolutionising" the way Wall Street invested money.

The total absence of a correlation between volatility and return for individual stocks is not the only thing that troubles this method and its exponents. Even more fundamental is the failure of volatility measures to remain constant over time. Any options trader will tell you immediately that volatility is not the same from day to day, nor hour to hour or even year to year. Volatility simply does not stay the same for any period of time and varies drastically from one time period to another. Stocks do not have a fixed volatility and hence it is absolutely impossible to use that factor to make meaningful changes to a portfolio unless you know what volatility is going to be; and we are no closer to finding a way to predict volatility than we are to being able to predict the general movement of prices.

Beta, as defined by Sharpe, Lintner and Mossin were shown to have no predictive power. The beta defined for one period differs drastically to that in the next and there is no way of using beta to predict future volatility.

Barr Rosenberg, a well respected researcher proposed a more sophisticated multifactor beta, including a large number of other inputs besides volatility to measure risk. These betas, called "Barr's Bionic Betas" proved as worthless as previous definitions in portfolio construction. Other betas were examined but none proved to have any usefulness at all for anything besides providing work for market statisticians.

The Capital Asset Pricing Model is based entirely on beta. Without a reliable beta you can't have CAPM any more than a value investor can buy stocks without knowing anything about assets or earnings. Somehow all this managed to be ignored until Eugene Fama, one of the original researchers who in 1973 had been right at the centre of the development of the Efficient Market Hypothesis, put out a new paper on risk and return in 1992. (Fama and French, "The Cross-Section of Expected Stock Returns" Journal of Finance 67 (1992), pp 427-465). Fama and French examined 9,500 stocks between 1963 and 1990, concluding that a stock's risk, measured by beta, was not a reliable predictor of performance. Fama stated "beta as the sole variable in explaining returns on stocks ... is dead. ... What we are saying is that over the last 50 years, knowing the volatility of an equity doesn't tell you much about the stock's return."

This was like the Pope announcing that there is no God, anyone who knows what a central role Fama's early 1970s work on EMH and MPT played would appreciate that this was an astounding development. As the Chicago Tribune put it: "Some of its best-known adherents have now become detractors."

If not volatility, then what? "What investors really get paid for is holding dogs." said Fama's coworker French. Their research found that stocks with lower price to earnings ratios and price to book ratios, as well as smaller capitalisation companies provided the highest returns over time. Stocks are more positively related to these measurements than to beta or other similar risk criteria.

Fama's words "beta is dead" reverberated around the world. As one finance professor put is in discussing the Fama and French findings:

Modern finance today resembles a Meso-American religion, one in which the high priest not only sacrifices the followers - but even the church itself. The field has been so indoctrinated and dogmatised that only those who promoted the leading model from the start are allowed to destroy it.

Other measures were developed do adjust returns by volatility to devise "risk adjusted" returns. I might return 40% over a few years but if I do this with sufficiently high volatility then someone who invested in treasury bills would have better risk adjusted returns. Remember that volatility, in its usual definition, is no different for upside or downside movements. If I achieved this with results ranging between +1% and +100% in any given year, but with no down years at all, then on the basis of that track record my strategy was obviously a risky one. Many contrarian and value investors whose track records include very little downside volatility but tend to make a lot of money when markets bounce have very poor "risk adjusted" returns as a result of this thinking.

Beta gives the appearance of a highly sophisticated mathematical formula but in reality it is data mining, looking at history you can find a number of factors that seem to be correlated, but these correlations are more often than not sheer coincidence. This is very bad science. I learned while doing my own studies that it is wrong to confuse correlation with causality, and wrong to just assume that correlations can be extrapolated to the future. Perhaps other researchers in finance and economics should study for a degree in the physical sciences as I did, maybe they don't teach this concept in economics.

Modern Portfolio Theory is based on a number of assumptions. Mathematically you would expect any conclusions to be drawn from the model to be correct as long as the assumptions are correct. In science we develop basic theories and understand basic principles. As long as the fundamental pieces fit, equations can be manipulated to provide new insights. This is why now that quantum mechanics and relativity are fairly well understood a large proportion of scientific discovery is purely mathematical. As long as the theory is correct you can make new discoveries by putting the theory into a mathematical model and giving it all a good shake. Physicists have found hundreds of subatomic particles that were originally predicted and described in complete detail by mathematics.

So what assumptions and fundamentals does Modern Portfolio Theory rely on? There are ten of them which are particular doozies. The following are key concepts around which MPT has been constructed:

There are no transaction costs in buying and selling securities. There is no brokerage, no spread between bidding and asking prices. You pay no taxes of any kind and only "risk" plays a part in determining which securities an investor will buy.

An investor can take any position of any size in any security he wishes. No one can move the market and liquidity is infinite. You can buy a trillion dollars worth of stock in a small speculative mining stock or buy one cent worth of Berkshire Hathaway. Nothing stops you from taking positions of any size in any security.
The investor does not consider taxes when making investment decisions, and is indifferent to receiving dividends or capital gains.

Investors are rational and risk adverse. They are completely aware of all risk entailed in an investment and will take positions based on a determination of risk, demanding a higher return for accepting greater volatility.
Investors, as a group, look at risk-return relationships over the same time horizon. A short term speculator and a long term investor have exactly the same motivations, time horizon and profit target. Regardless of who you are, you will always give an investment the same amount of time to work out and volatility will be your only concern.

Investors, as a group, have similar views on how they measure risk. All investors have the same information and will buy or sell based on an identical assessment of the investment and all expect the same thing from the investment. A seller will be motivated to sell only because another security has a level of volatility corresponding to their desired return. A buyer will make a purchase because this security has a level of risk corresponding to the return that he wants.

Investors seek to control risk only by the diversification of their holdings.
All assets, including human capital, can be bought and sold on the market.
Investors can lend or borrow at the 91-day T-bill rate - the risk-free rate - and can also sell short without restriction.
Politics and investor psychology have no effect on the markets.

In fact transaction costs have a major effect on whether you want to be a long term or short term investor, and taxes have a major impact on what kind of investments make sense. Liquidity is a major factor in keeping most people out of thinly traded issues and the difference between dividends and capital gains very much affects the type of securities an investor will buy.

Investors are not rational, they go for "hot" sectors and markets boom and bust regularly because of speculative excesses. Many people will buy stocks based only on rumour or hunches, the market for thinly traded issues would be wiped out if people really appreciated the true situation of the companies being traded.

Who could argue that a day trader and Warren Buffett would see eye to eye on the outlook of a stock. Does a long term investor buy the same stocks as a trader?

Only the government can borrow at the T-bill rate. No other investor in the world can borrow money at these rates unless they have some special concession. Short selling is illegal or severely restricted in many countries.

Three hundred years of Tulipomania, South Seas bubbles, Real Estate rushes, gold rushes, concept stocks, junk bond busts, dot coms and Asian Crises have shown that politics and psychology have a major effect on markets.

But don't let any of this dissuade you from believing in Modern Portfolio Theory or looking up tables of beta and alpha for various stocks. After all, almost every university throughout the world still teaches MPT to finance and economics students, fund rating services such as Morningstar allocate stars based to a large degree on "risk adjusted" returns, fund managers structure their portfolios based on the Capital Asset Pricing Model, which is a key part of Modern Portfolio Theory, and financial planners do their best to pigeonhole clients into one of five "risk profiles" where all but the most "aggressive" permanently devote large proportions of their portfolio to "low risk" investments such as cash and bonds, even though we do know that taxes and inflation make these classic loser's investments.

MPT is enshrined to the point that it is included in legislation. Risk profiles are an essential part of financial planning, and if I, as a financial planner, were to recommend a portfolio made entirely of stocks, I would probably be sued successfully if the market fell, even if the investor had a very long term outlook. ASIC requires diversification and require us to provide our clients with volumes of data calculated with the Capital Asset Pricing Model. The Diploma of Financial Planning, as well as many similar industry qualifications for those who wish to be advisers or analysts or portfolio managers teaches the Efficient Market Hypothesis and MPT as gospel.

The "prudent man rule", a concept where a fiduciary (professional funds manager) is obliged to invest in "safe" assets is based on a definition of risk that only goes as far as maintaining dollar amounts of a portfolio, even if purchasing power is lost. In our rush to protect funds, we find that a volatility definition of risk is important, and even though inflation and taxes may well destroy an investor's real wealth, as long as dollars are preserved a fiduciary can be said to have acted prudently; hence the popularity of bonds and cash in long term portfolios.

What about those studies that show that nobody in history has outperformed the market by a statistically significant amount?

Supporters of the Efficient Market Hypothesis gleefully point out that by their reckoning no investor in history has ever turned in a statistically significant outperformance of the market averages over a long period of time. Even Warren Buffett who has more or less consistently outperformed since the 1950s is regarded as a statistical freak, the guy that managed to flip heads on two coins one hundred times in a row out of sheer dumb luck.

What is this "statistical significance" and most importantly, what sort of performance does one need to turn in to achieve a statistically significant result?

David Dreman wrote about this in Contrarian Investment Strategies: The Next Generation in a section entitled "The Vanishing Support for EMH", so just how does a person go about proving that they can outperform the market, to the satisfaction of all parties?

The biggest problem with statistical significance is that it is a weak tool when there is very little data available. Statistics was designed for use with large sets of numbers, you want thousands of data points in your survey and simply put most money managers haven't been in the industry long enough to have thousands of quarterly performance figures out just yet!

When you have smaller data sets, you need to be looking for larger differences to be flagged as statistically significant. When you have one million data points you won't need very much of an outperformance to show up on a researcher's screen at the 95% confidence level (generally regarded as the minimum acceptable level of statistical significance), so when someone has clocked up 250,000 years worth of quarterly data it will be blindingly obvious to even the statisticians that his long term average return was pretty good! For most managers that have a career of maybe 30 years, that is only 120 data points. You need to be looking for a very severe outperformance to get good statistical significance with a track record so short.

One of the most important studies upon which the Efficient Market Hypothesis first drew support used a technique by Jensen (one of the important mutual fund investigators). One study showed that using the Jensen technique out of 115 funds only one demonstrated superior performance.

To even show up on the screen, the manager had to have a past performance beating the market by no less than 5.83% annually for 14 years! Books get written about guys that manage to outperform the market by only a couple of percent (ie John Neff, Peter Lynch), so I think it would be fair to say that this test of performance is unrealistic. Only someone in the league of Buffett or Templeton could hope to show up with such a high cutoff, and then you'll just get a few remaining sour grapes claiming that since only two people in history have ever achieved this performance it probably just comes down to dumb luck.

In another study using risk adjustment techniques the researchers showed that at the 95% confidence level it was impossible to tell whether a portfolio that was up 90% over ten years had outperformed one that was down 3%. (!!) They noted that given a reasonable level of annual outperformance and volatility, it takes about 70 years of quarterly data to achieve statistical significance at the 95% level.

Lawrence Summers, later Deputy Secretary of the Treasury of the United States under the Clinton administration estimated that it would require 50,000 years of data to disprove the Efficient Market Hypothesis to the satisfaction of the stalwarts.

Having said all of this...

I take the view that the market is not efficient, indeed there are numerous "anomalies", such as the outperformance of value stocks compared to growth stocks, various autocorrelation studies have established that momentum and regression to the mean are commonly seen, and that small companies do seem to outperform large companies.

The mere existence of Warren Buffett and John Templeton does prove that it is possible to select stocks and earn a higher return than an index fund. On a more practical level though, it is very clear that there aren't many of these people around, and it is also clear that identifying such individuals in advance (when selecting a fund manager to put your money with) is very hard.

Moderate academics acknowledge that there are inefficiencies, "free lunches" as some put them, in market prices. What few people doubt though is that spotting them requires more skill than most people have and that for the most part stocks are efficiently priced most of the time. As one researcher put it, there may be free lunches but you'll starve to death waiting for them.

One hedge fund manager I spoke to the other day had these words to say, "we find that 80% of all stocks are efficiently priced, we look for the 20% that aren't." It is fair to say that the majority of stocks are efficiently priced and that an index fund will thus be a relatively efficient vehicle. Maybe this hedge fund manager can identify the 20%, maybe he can't. The question that we as investors need to think about is whether we feel confident that the managers we invest with (or us, if you DIY) can successfully identify the 20% of incorrectly priced stocks and profit from them. Some can, obviously, but knowing if our strategy will work in advance, given that most active strategies don't, is the million dollar question.

A second question is whether these inefficiencies are really so profitable that they are even worth going for once identified. If your active strategy leads to more frequent realisations of capital gains then the loss of tax efficiency might do more harm than your strategy does good.

While I do encourage readers to study the great investors, I also encourage anyone that does not, after much honest self assessment, feel that they are not quite up to Buffett's standards, to consider an indexed approach instead.

I personally do keep an eye out for free lunches, but in the mean time I am happy enough to leave most of my money invested across a variety of index funds, including in particular value index funds. In the next article, I'll bring you a little closer to the state of the art in Modern Portfolio Theory. Chuck out your CAPM and burst your beta, the truly chic academics are now seeking to explain why value stocks outperform, given that they aren't actually more volatile.

http://www.travismorien.com/FAQ/portfolios/mptcriticism.htm