Best Practices in Research for Quantitative Equity Strategies

Abstract

The authors examine the research process and principles underlying successful models used in quantitative equity strategies. They identify three key factors they see contributing to improved empirical work: 1) making research design a top priority, 2) making new, more extensive datasets available, and 3) making advances in computational areas such as econometrics, machine learning, and statistics. The authors explain these key factors and also share insights on how to integrate market dynamics, data, research design, advance modeling techniques, and economic/financial introspection into the research process.

TOPICS: Quantitative methods, derivatives, portfolio management/multi-asset allocation