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Efficient Market Theory
Nassim Nicholas Taleb, author of The Black Swan (2007), correctly argues that highly unexpected events are much more likely than accounted for in risk management models used today, i.e., use distributions with “fat tails.” However the real problem with current risk management models goes much deeper, rather, they employ current academic theory of the efficient market theory (EMT) to depict markets as efficient, always in equilibrium and self correcting where security prices simply react to random news releases. The EMT models individual security price movements as “independent random variables” where purchase or sale is a “zero net present value transaction,” resulting in neither the buyer nor seller having an advantage. Consequently, security trading is modeled like casino gambling where price volatility determines risk assessment. The EMT concludes that because prices always fairly reflect intrinsic value and it is impossible to know what markets are going to do, consequently, fundamental analysis isn’t cost effective. With all due respect to my academic colleagues, the EMT model is both naïve and specious, i.e., it relies on incorrect premises and, therefore, cannot correctly model market risk. A discussion follows.
Markets are not always in equilibrium nor self correcting but rather are a discounting mechanism, i.e., professional traders look ahead and bid prices either up or down prior to earnings and/or economic news announcements; that is why prices can go up on bad news and down on good news. Security prices from day to day seem random, however, diversification cancels out unsystematic risk, therefore, markets as a whole only have systematic risk. Using a diversified market portfolio, monthly rather than daily data, trend lines and conditional probabilities based on fundamental analysis correctly models systemic market risk; thereby disqualifying the flawed EMT’s reliance on securities’ price frequency and the use of price volatility as a proxy for portfolio risk which is not sufficient information when hedging positions. Financial Products computer models depend upon the EMT, demonstrating why incorrect theories have major consequences, conceivably, even being the root cause for this GREAT RECESSION.
Financial risk modeling has an interesting almost haphazard history which further complicates bank “stress testing” ongoing today. Harry Markowitz, the father of modern portfolio theory, for which he received a Nobel Prize in Economics in 1990, in his 1952 paper in The Journal of Finance assumed market efficiency, because his entire theory relied on stock prices being random variables, and a normal distribution to model stock returns because mean and variance would then be the only two measures that investors need consider. Mean, is desirable, and equated to “expected return” and variance of return, is undesirable, and assumed to adequately model “ risky-ness of the investment.” Markowitz never explained why variance/standard deviation measures of price volatility should be a good proxy for the “risk of loss,” although academe readily accepted it.
Warren Buffett criticized using volatility measures for risk measurements because that precludes knowing anything about the company’s intrinsic value. A company’s stock which is highly volatile would be considered mean-variance risky, however, if that same company had a very high intrinsic value and the stock price dropped to the low of its range, Buffett would then rightly consider the company to be a buy and a relatively risk-less purchase. Buffett’s explanation is logical while Markowitz has a mathematical solution in search of a problem, or as Yves Smith would say, “computational convenience trumped empirical findings.”
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