Factor Investing in Corporate Bond Markets: Enhancing Efficacy Through Diversification and Purification!

Abstract

We show that factors from value, quality, low-risk, and momentum styles play an important role in explaining the cross-section of corporate bond expected returns for the US and Euro Investment Grade and US BB-B Nonfinancial High Yield universes. We demonstrate the importance of purifying factor data by neutralizing a number of risk biases that are present in the factors: controlling for sectors, option-adjusted spread, duration, and size biases significantly increase the predictive power of style factors. We propose a new simple approach for efficiently neutralizing the biases from multiple risk variables and demonstrate its superiority relative to stratified sampling and optimization as alternative control methods. We also measure the added value from diversifying the number of factors in each style. Finally, we show that the results are robust in relation to transaction costs and can be used to design strategies that aim at outperforming traditional benchmark indexes.

TOPICS: Analysis of individual factors/risk premia, factor-based models, style investing

Key Findings

• • Factors from value, quality, low-risk, and momentum styles play an important role in explaining the cross-section of corporate bond expected returns for the US and Euro Investment Grade and US BB-B Nonfinancial High Yield universes.

• • The forecasting efficacy of style factors increases significantly if biases such as sectors, option-adjusted spread, duration, and size in the factor data are neutralized. Diversifying the number of factors in each style also significantly improves the forecasting efficacy.

• • We propose a new simple approach for increasing the forecasting efficacy of style factors by efficiently neutralizing the biases from multiple risk variables. We demonstrate the superiority of this approach over stratified sampling and optimization.