Cross-Sectional Factor-Based Models and Trading Strategies

JOSEPH A. CERNIGLIA

Visiting Researcher, Courant Institute of Mathematical Sciences, New York University

PETTER N. KOLM, PhD

Director of the Mathematics in Finance Masters Program and Clinical Associate Professor Courant Institute of Mathematical Sciences, New York University

FRANK J. FABOZZI, PhD, CFA, CPA

Professor of Finance, EDHEC Business School

Abstract: Quantitative asset managers construct and apply models that can be used for dynamic multifactor trading strategies. These models incorporate a number of common institutional constraints such as turnover, transaction costs, sector, and tracking error. Approaches for the evaluation of return premiums and risk characteristics to factors include portfolio sorts, factor models, factor portfolios, and information coefficients. Several techniques are used to combine several factors into a single model—a trading strategy. These techniques include data driven, factor model, heuristic, and optimization approaches.

In the construction of factor models, factors are constructed from company characteristics and market data. In this entry, we explain and illustrate how to include multiple factors with the purpose of developing a dynamic multifactor trading strategy that incorporates a number of common institutional constraints such as turnover, transaction costs, sector, and tracking error. For this purpose, we use a combination of growth, value, quality, and momentum factors. ...

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