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We study the empirical determinants of Credit Default Swap (CDS) spreads through quantile regressions. In addition to traditional variables, such as implied volatility, put skew, historical stock return, leverage, profitability, and ratings, the results indicate that CDS premiums are strongly determined by CDS illiquidity costs, measured by absolute bid-ask spreads. The quantile regression approach reveals that high-risk firms are more sensitive to changes in the explanatory variables that low-risk firms. Furthermore, the goodness-of-fit of the model increases with CDS premiums, which is consistent with the credit spread puzzle.

This paper offers a rational explanation for the puzzling empirical fact that stock returns decrease in the volatility of liquidity. We model liquidity as a stochastic price impact process and define the liquidity premium as the additional return necessary to compensate a multi-period investor for the adverse price impact of trading. The model demonstrates that a fully rational, utility maximizing, risk averse investor can take advantage of time-varying liquidity by adapting his trades to the state of liquidity. We provide new empirical evidence supportive of the model. * We are grateful for the helpful comments of Dong

This paper studies how the state of the banking sector influences stock returns of nonfinancial firms. We consider a two‐factor pricing model, where the first factor is the traditional market excess return and the second factor is the change in the average distance to default of commercial banks. We find that this bank factor is priced in the cross section of U.S. nonfinancial firms. Controlling for market beta, the expected excess return for a stock in the top quintile of bank risk exposure is on average 2.83% higher than for a stock in the bottom quintile.

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