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We provide a comprehensive study on the cross-sectional predictability of corporate bond returns using big data and machine learning. We examine whether a large set of equity and bond characteristics drive the expected returns on corporate bonds. Using either set of characteristics, we find that...
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Long-term reversals in corporate bonds are economically and statistically significant in a comprehensive sample spanning the period 1977 to 2017. Such reversals are stronger for bonds with high credit risk and more binding regulatory, capital, and funding liquidity constraints. Bond long-term...
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We investigate the cross-sectional determinants of corporate bond returns and find that downside risk is the strongest predictor of future bond returns. We also introduce common risk factors based on the prevalent risk characteristics of corporate bonds -- downside risk, credit risk, and...
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We provide time-series and cross-sectional evidence on the significance of a risk-return tradeoff in the corporate bond market. We find a significantly positive intertemporal relation between expected return and risk in the bond market and the time-series predictability is driven by aggregate...
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We investigate whether the distributional characteristics of corporate bonds predict the cross-sectional differences in future bond returns. The results indicate a significantly positive (negative) link between volatility (skewness) and expected returns, whereas kurtosis does not make a robust...
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