Better Investing Through Factors, Regimes and Sensitivity Analysis

100 Pages Posted: 30 Jan 2015

Date Written: January 25, 2015


Recent periods of market turbulence and stress have created considerable interest in credible alternatives to traditional asset allocation methodologies. It would be preferred if portfolios can be decomposed into components that can be directly connected to independent risks and individually rewarded by the market for their level of risk. This can be achieved through factor-based investing, which relies on the observation that most return and risk characteristics for all asset classes can be well explained by particular building blocks, or factors.

We describe main features of factors, factor investing and factor models, with emphasis placed on practical topics such as selection of significant factors associated to specific asset classes, differentiating between factors, anomalies or stylized facts, and preference for composite portfolios based on combining factors. We have also analyzed implementation details and the factor risk parity strategy.

Then we consider improvements to factor-based investing through regime switching and sensitivity analysis. We present theoretical and practical frameworks for Markov switching models and for sensitivity analysis, and rely on representative examples to illustrate the benefits of efficiently incorporating regimes and sensitivity analysis into portfolio management.

The final section describes features of good testing procedures for portfolio behavior and performance, in contrasts with possible testing pitfalls.

Keywords: factor investing, factor models, regime switching, sensitivity analysis, backtesting, portfolio management, risk management, asset allocation, risk parity, parameter estimation, optimization, diversification, smart beta, Monte Carlo, testing, stress, tail risk

JEL Classification: C11, C12, C13, C14, C15, C51, C52, C63, G11, G12

Suggested Citation

Homescu, Cristian, Better Investing Through Factors, Regimes and Sensitivity Analysis (January 25, 2015). Available at SSRN: or

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