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Seven Quantitative Insights into Active ManagementA SummaryOver the past seven newsletters we have presented seven quantitative insights into active management. We can summarize these seven insights by observing how they all fit into the process of active management. FIGURE 1 illustrates this process, which we define generally as efficiently utilizing superior information. The Research stage involves the search for superior information. This information must be better than consensus information (Insight 1: Active Management is Forecasting). We can improve our chances for success by investigating many signals (Insight 3: The Fundamental Law of Active Management). At the same time, we need to avoid data mining (Insight 5: Data Mining is Easy). The goal of this Research stage is a strategy with a high information ratio (Insight 2: Information Ratios Determine Value Added). The Refinement stage takes our research signals and converts them to alphas by controlling for skill, volatility, and expectations (Insight 4: Three-Part Alphas). The Portfolio Construction and Rebalancing stage and the Trading stage implement the strategy. Here the goal is to lose as little of the intrinsic strategy value as possible (Insight 6: Implementation Subtracts Value). The Performance Analysis stage looks at results, identifying (imperfectly) what worked and what didn’t work, in part as feedback to Research (Insight 7: It’s Hard to Distinguish Skill from Luck). It is useful to note that while we have presented (and derived) these seven insights as “quantitative,” they apply to all managers: fundamental, quantitative, top-down, bottom-up, equity, bond, and so forth. Finally, let me point out that we have called this series “Seven Quantitative Insights...” and not “The Seven Quantitative Insights into Active Management.” This series has omitted some known insights. And, as a researcher, I will always claim that there remain more insights to uncover.
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