Portfolio Management Traditional Approach Depth Regime shifts Signal identification Qualitative factors Quantitative Approach Breadth Discipline Verification Risk management Lower fees Although they have views on fewer companies, traditional managers tend to have more in-depth knowledge of the companies they cover. Unlike a computerized model, they should know when data are misleading or unrepresentative. Traditional managers may be better equipped to handle regime shifts and recognize situations where past relationships might not be expected to continue (e.g., where back tests may be unreliable). Based on their greater in-depth knowledge, traditional managers can better understand the unique data sources and factors that are important for stocks in different countries or industries. Many important factors that may affect an investment decision are not available in any database and are hard to evaluate quantitatively. Examples might include: management and their vision for the company; the value of patents, brands, and other intangible assets; product quality; or the impact of new technology. Because a computerized model can quickly evaluate thousands of securities and can update those evaluations daily, it can uncover more opportunities. Further, by spreading their risk across many small bets, quantitative managers can add value with only slightly favorable odds. While individuals often base decisions on only the most salient or distinctive factors, a computerized model will simultaneously evaluate all specified factors before reaching a conclusion. Before using any signal to evaluate stocks, quantitative managers will normally back test its historical efficacy and robustness. This provides a framework for weighting the various signals. By its nature, the quantitative approach builds in the notion of statistical risk and can do a better job of controlling unintended risks in the portfolio. The economies of scale inherent in a quantitative process usually allow quantitative managers to charge lower fees. management, we will primarily apply a quantitative framework for describing the EPM process in the rest of this chapter. FORECASTING STOCK RETURNS, RISKS, AND TRANSACTION COSTS Developing good forecasts is the first and perhaps most critical step in the investment process. Without good forecasts, the difficult task of forming superior portfolios becomes nearly impossible. In this section we discuss how to use a