RISK CONTROL

Even if the expected return is modeled properly at the individual stock level, the bottom line of implementable investment strategies is evaluated by an acceptable level of risk-adjusted portfolio excess returns. As most institutional portfolios are benchmarked, the goal is to minimize tracking error (standard deviation of excess returns), given some level of portfolio excess return. Consequently, risk control becomes technically much more complex than the conventional efficient portfolio concept. As shown by Richard Roll, an optimal portfolio that minimizes tracking error subject to a level of excess return is not a mean-variance efficient portfolio.19 It should be noted that, due to the objective and competitive nature of the quantitative approach in its strong form, most models produce similar rankings in expected returns. The variation in performance among quantitative portfolios is mainly attributed to a superior risk control technology.

One commonly used, but less preferred practice in risk management is often performed right at the stage of identifying the model for expected returns. It involves revising the estimates from the model to explain the actual return. The purpose is to control the risk by attempting to reduce the estimation error for the model of expected returns. This approach has several flaws. First, in most cases, the procedure of revising the parameter estimates (from the model of actual returns) so they can be used in the model of expected returns ...

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