Investment Risk and Return: Efficient Markets, Rational Investors

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In previous blogs, we discussed the concepts of alpha and beta in the context of hedge fund investment returns.  Recall that alpha refers to that portion of total return attributable to an investment manager’s skill; beta is simply the return due to an investment’s exposure to market risks. A third component, random fluctuations, essentially goes to zero over time and is usually ignored in this discussion. One of the biggest questions in the hedge fund industry today is the role, if any, of alpha in investment returns, and how much is the alpha contribution worth?

One of the earliest (Louis Bachelier, 1900) theories of investment returns is the efficient market hypothesis (EMH). EMH posits that over time it is impossible to predict markets, and hence all market risk is beta risk, that alpha generation is an illusion.  Further refinement in the 1960’s stated that prices (and thus returns) take a “random walk” and that investors cannot hope to outperform the market on a risk-adjusted basis.  The underpinning of EMH is that investors are rational, markets are efficiently-priced because future prices cannot be predicted from past performance and markets can instantly respond to new information, perhaps even inside information.

What exactly makes an investor rational? Three factors have been identified:

1)      Asset integration: investors prefer securities in their portfolios to alternatives not in their portfolios.  Otherwise, they would change their portfolios.

2)      Risk aversion: given two investments with equal expected returns, an investor will always choose the less risky alternative.

3)      Rational expectation: investors incorporate all available information in an unbiased and coherent fashion.

EMH come in three flavors:

1)      Weak form: past prices do not influence future prices, stock charts are not predictive of trends and technical analysis is, on average, useless.  Investors cannot systematically profit from market inefficiencies because prices movements are essentially random. However, there are studies of short-term stock price trends that are at odds with weak-form efficiency.

2)      Semi-strong form: incorporates the weak form and further states that excess returns cannot be systematically extracted from new information.  This implies that fundamental analysis is futile, and that markets adapt instantly to news.

3)      Strong form: incorporates the semi-strong form plus states that there is no advantage to inside information because that information is already in the security’s price.

EMH lost favor in the 1990’s when researchers and behavioral finance economists challenged its basic assumptions. For instance, stocks with low price-to-earnings ratios or with dividend increases were found to outperform the general market. And as anyone who experienced the market fluctuations of 2008 can testify, it is dangerous to assume that current prices efficiently reflect all available information.

Most observers have rejected the strong form, and many question all forms of EMH. Behavioral finance looks at human failings, such as hubris, bias, loss aversion, and overreaction, to question the basic validity of EMH. Studies of low P/E stocks found above-average returns not attributable to higher betas.  Other studies have shown that poor-performing stocks often reverse into superior performers without exhibiting the higher beta needed to justify the higher returns. The implication that human psychology creates market inefficiencies implies that alpha-based returns are possible.  A further refinement differentiates certain markets, such as currencies, are more efficient than others and that alpha profits can only be extracted from smaller, less efficient markets.

George Soros has argued for the recognition of a reflexive relationship between the market’s inability to accurately forecast future returns and the role the markets play in shaping those returns.  However, this does not necessarily imply that an alpha-based profit can be extracted.

In the next article in this series, we’ll look more closely at alpha and beta in the context of asset pricing models.

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Copyright 2010 Eric Bank, Freelance Writer

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