CONSTRUCTING, TRADING, AND EVALUATING PORTFOLIOS

To maximize implementation of the model's insights, the portfolio construction process should consider exactly the same dimensions found relevant by the stock selection model. Failure to do so can lead to mismatches between model insights and portfolio exposures.

Consider a commercially available portfolio optimizer that recognizes only a subset of the variables in the valuation model. Risk reduction using such an optimizer will reduce the portfolio's exposures only along the dimensions the optimizer recognizes. As a result, the portfolio is likely to wind up more exposed to those variables recognized by the model, but not the optimizer, and less exposed to those variables common to both the model and the optimizer.

Imagine an investor who seeks low-P/E stocks that analysts are recommending for purchase, but who uses a commercial optimizer that incorporates a P/E factor but not analyst recommendations. The investor is likely to wind up with a portfolio that has a less-than-optimal level of exposure to low P/E and a greater-than-optimal level of exposure to analyst purchase recommendations. Optimization using all relevant variables ensures a portfolio whose risk and return opportunities are balanced in accordance with the model's insights. Furthermore, the use of more numerous variables allows portfolio risk to be more finely tuned.

Insofar as the investment process, both stock selection and portfolio construction, is model-driven, ...

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