Dynamic hedging strategies, a critical element of portfolio management, incorporate correlations among cross-market asset returns. Prior researchers have focused on equity and credit market relationships at the aggregate level. Because credit default swaps are increasingly used to execute firm-specific trading strategies, the authors attempt to better understand the relationship between equity returns and credit default swap spread changes at the firm level.
The authors attempt to better understand the firm-level relationship between equity returns and credit default swap (CDS) spread changes. They find substantial time variation in the correlation dynamics as explained by discount rate news, particularly over short time horizons. The importance of cash flow news for CDS spread changes increases with longer time horizons. Furthermore, the authors discover that the correlations between equity returns and CDS spread changes exhibit different behaviors during crisis and noncrisis periods. Lastly, they find that correlations between equity returns and CDS spread changes are greater for speculative-grade firms than for investment-grade firms.
How Is This Research Useful to Practitioners?
The authors quantify the correlation between equity returns and changes in CDS spreads at the firm level. Their findings build on prior research that has been primarily focused on this relationship at the aggregate level. Moreover, they are able to discover variables that influence this correlation. Specifically, the results indicate that discount rate news is a significant driver of changes in correlations whereas cash flow news represents a smaller influence. Diving deeper into discount rate news, the authors find that changes in risk premium appear to have the most significant impact. They conclude that these observed correlations are stronger during crisis periods.
These results could help portfolio managers and various market participants better understand and implement cross-market dynamic hedging strategies. Not only should portfolio managers understand the joint-price behavior between equity and credit market instruments, but they must also appreciate how regime changes and other outside influences can alter asset return correlations. The authors’ findings have direct application to mean–variance asset allocation, risk management, and capital structure arbitrage strategies.
How Did the Authors Conduct This Research?
The authors use four primary data sources: CRSP, Compustat, I/B/E/S, and Markit. They observe data from 2001 through 2013. CDS spreads are obtained for senior unsecured debt for 988 firms from Markit. Using CRSP data, the authors then exclude firms with fewer than 100 observations, resulting in 895 firms. They use the average rating with daily frequencies during the sample period. Data from I/B/E/S are used for analyst forecasts. Firms that were delisted during the sample period are removed, as are firms with fewer than 16 months of CDS spread observations.
The final sample includes 516 firms, of which 389 are investment grade and 127 are speculative grade. The authors observe that firms in the 895-firm larger sample are riskier than those in the final sample. Moreover, firms in the final sample generally have larger CDS spreads and smaller market capitalizations and use more leverage. Equity volatility and book-to-market ratios are similar between the two samples.
The authors provide a detailed analysis of the correlation between equity returns and changes in CDS spreads. Although prior research has been focused on this relationship at the aggregate level, the authors go a step further by exploring this relationship at the firm level. Ultimately, I would love to see further research expand the scope of these findings in terms of specific sector impacts as well as any international influences.