We study the dynamic impact of idiosyncratic volatility and bond liquidity on corporate bond spreads over time and empirically disentangle both effects. Using an extensive data set, we find that both idiosyncratic volatility and liquidity are critical mainly for the distress portfolios, i.e., low-rated and short-term bonds; for others only volatility matters. The effects of volatility and liquidity shocks on bond spreads were both exacerbated during the recent financial crisis. Liquidity shocks are quickly absorbed into bonds prices; however, volatility shocks are more persistent and have a long-term effect. Our results overall suggest significant differences between how volatility and liquidity dynamically impact bond spreads.

Researchers are often interested in modeling binary decisions made by firms (e.g., the yes or no decisions to split the shares, initiate a dividend, or acquire another firm) as functions of economy-wide variables (common factors). Although factor models for continuous dependent variables are used widely, the toolkit of a financial researcher does not contain a generally accepted methodology that allows estimating factor models for binary dependent variables. In this paper, we study such a methodology. Using simulations, we identify data characteristics that allow for reliable estimates of factor parameters and conclude that the methodology is appropriate for the panel datasets of the type often used in finance. As an illustration, we use the methodology to address a currently debated issue of common factors in firms’ decisions to split their shares.