• 525 days Will The ECB Continue To Hike Rates?
  • 526 days Forbes: Aramco Remains Largest Company In The Middle East
  • 527 days Caltech Scientists Succesfully Beam Back Solar Power From Space
  • 927 days Could Crypto Overtake Traditional Investment?
  • 932 days Americans Still Quitting Jobs At Record Pace
  • 934 days FinTech Startups Tapping VC Money for ‘Immigrant Banking’
  • 937 days Is The Dollar Too Strong?
  • 937 days Big Tech Disappoints Investors on Earnings Calls
  • 938 days Fear And Celebration On Twitter as Musk Takes The Reins
  • 940 days China Is Quietly Trying To Distance Itself From Russia
  • 940 days Tech and Internet Giants’ Earnings In Focus After Netflix’s Stinker
  • 944 days Crypto Investors Won Big In 2021
  • 944 days The ‘Metaverse’ Economy Could be Worth $13 Trillion By 2030
  • 945 days Food Prices Are Skyrocketing As Putin’s War Persists
  • 947 days Pentagon Resignations Illustrate Our ‘Commercial’ Defense Dilemma
  • 948 days US Banks Shrug off Nearly $15 Billion In Russian Write-Offs
  • 951 days Cannabis Stocks in Holding Pattern Despite Positive Momentum
  • 952 days Is Musk A Bastion Of Free Speech Or Will His Absolutist Stance Backfire?
  • 952 days Two ETFs That Could Hedge Against Extreme Market Volatility
  • 954 days Are NFTs About To Take Over Gaming?
  1. Home
  2. Markets
  3. Other

Beta(ful) Market Hypotheses

Market DNA Blog October 22 2009

In my many years as a derivative trader and hedge fund manager, I forged a solid and long lasting relationship with risk. Like a beautiful but dangerous woman, risk permeated my professional life -- a constant courtship leading me to many attempts at fully understanding its mysterious ways... a never ending effort!

The theoretical foundations of risk analysis were laid in business school where I diligently learned of Alpha and Beta, Random Walks and Efficient Market Hypotheses (EMH). These theories were elegant and pure, like a fresh mantle of snow they seem to perfectly cover all market uncertainties and provided a boost of confidence to a young man ready to leave his mark in Wall Street.

Yet, the one reason why I was fascinated by the markets was the mesmerizing and intellectually challenging example of hedge fund manager extraordinaire George Soros. His book "The Alchemy of Finance" seemed to directly contradict EMH and his track record seemed to be damning evidence. Nevertheless, one of my first large successes came from the application of the bell curve to index returns for an option strategy. It worked like a charm in the roaring late nineties.

This initial success aside, every night I could not shake off that feeling of disconnect from theory to practice. Yogi Berra once said: "In theory there is no difference between theory and practice, in practice there is." Indeed, while the trading model was successful, the distribution of returns seemed way out of line with even a fat tail distribution. Adding to my discomfort it was the clear pattern of price dependency upon past changes (the H factor as Mandelbrot defines it) versus the theory of price randomness.

In 1999 and in 2000 we witnessed a ridiculous bubble in internet and technology stocks and a consequent blow up -- a dynamic that really should not have happened in the EMH universe. During 1999 I had decided to tweak my model and added heavy behavioral components. I think such changes saved me from terminal disaster in 2001, 2002 and more recently 2008.

In spite of evidence of misleading logic and cracks in the foundation behind the concepts of Beta and EMH, the theories are still wildly popular among academics. Academic politics and group thinking may be the cause; after all, almost every economist in the country is one way or the other on the Federal Reserve payroll for example. Yet Beta and EMH are now under attack not only by behavioralists but by mathematicians as well. Benoit Mandelbrot, one of the most influential mathematicians of our times, is again very vocal -- he started his critique 40 years ago and was derided by the mainstream---against these alluring but ultimately deceiving theories. Paul Wilmott also has been active in his criticism.

The idea that equity returns are random and therefore should be expected to fall in line with Gaussian distribution models is a bizarre conceptual starting point. While many natural events follow such distribution, why would something like investment returns follow a statistical order? Aren't stocks prices the result of fear and greed? Aren't financial markets the making of highly emotional beings? Isn't information asymmetry a major issue in financial markets? If anything, a clean statistical distribution should have been a last resort explanation for price formation rather then a starting point.

The real world does not move neatly -- markets are messy and simple mathematical relationships cannot capture reality. Equity prices can be explained by more logical (yet less statistical) structural and behavioral relationships. The Capital Asset Pricing Model armed with the false fortitude of the bell curve, reduces everything to one variable, Beta, to explain risk. Does one variable for a system as complex as financial markets make sense?

The buy and hold theory forced stocks in people's portfolios even when valuations were clearly off on the assumption of a consistent equity risk premium. This dynamic snowballed into the commercial explosion of beta-driven portfolios and unhooked Wall Street from any effort to produce intelligent analysis. Portfolio management reduced its legal liabilities and turned the large majority of the asset management universe into a huge marketing machine sucking in money flows which perpetuated the fallacy.

Beta is dead, long live Beta! Or perhaps it never existed. Maybe Beta was just a mirage of an industry looking for order and economies of scale. In the end, however, investment returns were proven to be influenced not by statistical distributions but by real issues.

Financial markets are highly reflexive as George Soros pointed out 25 years ago, and as a result, equity prices are dependent on the past. Momentum is a constant component of price formation. Also, the structural dynamics of the money management business are clearly heavy influences in stock prices -- the heavy hand of relative performance among money managers and the problem of career and business risk are two of the most important influences in the process of pricing investments. Tax issues and the changing regulatory environment are certainly more important drivers of prices than the Gaussian distribution. Not to mention social contagion, feedback loops, and of course changing technology.

The smart money manager must rely on a much more sophisticated framework than just the bell curve. I like to approach my investments following a 4 level framework (ex hedge fund manager turned media entrepreneur Todd Harrison follows a similar approach):

  • Structural overview. An analysis of the political, regulatory and technological environment.

  • Fundamental overview. Valuation analysis like Cyclically Adjusted Price/Earnings ratios and others.

  • Technical market make-up. Momentum, mean reversion, support and resistance, volatility.

  • Sentiment overview. A comprehensive behavioral analysis.

Comprehension of financial markets and the risks they inherently breed is a never ending process. As elegant as Beta and EMH were they were clearly not the answer.

Sources:
Benoit Mandelbrot, The (Mis)behavior of Markets, Basic Books, New York,2004
James Montier, Insight: Efficient Markets Theory Is Dead, FinancialTimes, June 24, 2009
George Soros, The Alchemy of Finance, Wiley and Sons, 1994

 

Back to homepage

Leave a comment

Leave a comment