Our intent is to dispel commonly held myths concerning the performance of investment methodologies. Our research has been carried out with meticulous care, in the finest tradition of scientific research. Any deficiencies in data are identified. The research design, the hypothesis, inferences, conjectures, contained within are intended to push the frontiers of investment knowledge; to challenge as well as supplement current academic thought.
In search of the Holy Grail ?
Do small capitalization stocks outperform large cap stocks after adjusting for risk? Does a value strategy outperform a growth strategy? What about contrarian approach? Almost everyone knows about January Effect, but only a handful of savants know the true variables that drive it. Do low P/E stocks do better? Is low price to book the great efficiency killing beta? Or did academic researchers fail to control the one common element in low P/E and low price to book - i.e. low price? A most significant and interesting variable of its own, low price has been ignored by academia. But it has important implications for investor behavior as does the issue of neglect. Except for work by Arbel, Carvell and Strebel, "neglect" has been neglected as a factor by academia. Small cap, beta, low price to book, low P/E, low price, and neglect present six dimensional problem. Will the "true" cause and effect please stand up? You cannot consider one without controlling for the other five. Cross correlations, mathematical discontinuities (negative book, EPS) and U-shaped distributions add to the fun.
We have been subjected to an endless mind-numbing array of journal, magazine and newspaper articles on these methodologies. Most of it has been misspecified and inadequately designed research. No one has yet to consider all six dimensions. Only recently have top academic researchers begun to consider and control for three (beta, small cap, price to book).
Should we relate returns to some measure of risk? There are two philosophical paths. We could use some risk based system to evaluate returns under the belief that higher returns should correlate with higher risk. So far so good. But how do we measure risk? Beta? Standard deviation? Or how much money we could lose? Who can agree? The second way is to consider results in the context of anomaly based behavioural systems. Except for the use of beta, we limit our measures and discussion of risk and instead concentrate on the explanatory power of the investment method or the abnormal returns associated with it. The problem of investing is that some investment methods are effective only in certain time periods, in certain types of markets. Methodologies also have different time horizons. Some can pick winners but can't identify losers. Other methods are highly correlated with each other. A method with the highest Information Coefficient (IC) or greatest excess return may be less valuable to an institutional investor that a method which provides a small stable positive return that is uncorrelated. It is a classic portfolio optimisation problem; what combination of investment methods will best satisfy the risk/reward profile and philosophy of a specific investor.
Hence, value is in the eye of the beholder.
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