Saturday, February 6, 2010

Thoughts on The Capital Asset Pricing Model Theory and Evidence - Earl Malvar

 The authors, Fama and French, are justified in cautioning students of finance to take the Sharpe-Lintner Capital Asset Pricing Model with a grain of salt. As any scientific endeavor would have it, even in the field of finance, empirical evidence and testing are critical in developing theories and fundamentals. Innovatively developed pricing models if simply based on previously faulty premises and models are clearly not sound and acceptable. The basics must first be set straight before the trail of thought can move forward. Though the CAPM provides an intuitive framework on which assets and securities can be valued, experiments and research have continually suggested that the CAPM and its assumptions are incomplete if not flawed. For one, defining a comprehensive and efficient market portfolio as a given is already a critical challenge to contend with because it is against which other variables will lean on. Furthermore, if indeed Markowitz highlights the importance of how the interrelationships of individual securities play on the risk-return profile of a portfolio, while past statistical data may be limited in revealing the probability of future price movements of various assets, then a certain set of securities may not necessarily be the much coveted proxy to the true efficient market portfolio. The elusiveness in pricing assets, especially those of interest to the investments community, is possibly due to the innumerable factors to consider. Although the human factor, aside from other overlooked or hard-to-quantify factors, may be “priced-in” on historical data that the CAPM and its other offshoots can take into account, these intangible factors serve as “wildcards” when looking at future fundamentals and price action. Perhaps an acceptable illustration would be in trading stocks, though some believe that technical analysis is more of an art than a science, practitioners have shown (though not always) that price charts of assets can approximate human behavior and psychology (among other things) in securities trading, without necessarily relying on measured or quantified data other than the price. Price action in itself is enough to encompass all data that matter. Dissecting the factors that influence the price movement, however, is not an activity that a technical analyst would spend his time on. A holy grail in valuing assets is still up for discovery and exploration, if indeed attainable.

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