The relationship between the credit market and the volatility market for five European countries broke down during the global financial crisis that occurred in 2007–2009. But the relationship remained intact during the subsequent European debt crisis, which has implications regarding cross-hedges between credit and equity instruments.
The authors analyze the term structure of European corporate bond credit-default swap (CDS) spreads and the implied volatility surfaces, a 3-D plot of the volatility smile, a smile-shaped graph of the implied volatility and the option strike price, and the term structure of the volatility. These are constructed from European call and put options on the major European indices—FTSE100, DAX30, CAC40, MIB40, and IBEX35—from 2007 to 2012. The date range allows them to study the effectiveness of cross-hedges between the credit and equity derivatives markets during two crises. Hindsight shows that a more effective hedge of a European CDS position during the global financial crisis would have entailed using the US CDS market rather than the European volatility market; the European CDS markets also would have hedged US CDS positions more effectively.
How Is This Research Useful to Practitioners?
This research is useful to traders and risk management professionals who use credit and volatility derivatives to hedge systematic risk. Cross-hedging strategies depend on the correlation between credit and equity markets. Although the regression coefficients were significant during the global financial crisis, indicating that there was a correlation, the R2 implies minimal effectiveness of the hedge. A more effective hedge would have been the use of an instrument in the same type of market but from a different geographic location. Also, volatility factors have been found to better hedge credit factors than the other way around.
The regressions the authors perform on the second subsample, which captures the European debt crisis, result in a higher R2, which suggests a stronger relationship between CDS spreads and volatility even though Spain and Italy experienced severe turmoil during that time period. When the authors consider just the first volatility factor, it leads to an R2 of 13.4%, a result that is more than three times greater than the result found during the time of the global financial crisis. All three volatility factors together lead to an average R2 of 26%.
The authors note the importance of incorporating all three factors regardless of small relative eigenvalues because lower-order factors can significantly improve the quality of the hedge. They analyze CDS and suggest that collateralized debt obligations (CDOs) could be used because they may lead to more effective cross-hedges. Further research is also suggested to study the connection between the credit and volatility markets at the firm level.
How Did the Authors Conduct This Research?
The CDS spreads on corporate bonds for the United Kingdom, Germany, France, Italy, and Spain are collected as daily time series from Markit at maturities of 0.5, 1, 2, 3, 5, 7, and 10 years for 23 May 2007 to 17 September 2012. The sample period is split into two subsamples to capture the crises; 23 May 2007 to 31 December 2009 captures the US credit crunch and the global financial crisis, and 1 January 2010 to 17 September 2012 captures the European debt crisis that mostly affected Italy and Spain. Daily prices for all available European call and put options of the major European indices and US market are from Datastream; the authors use only out-of-the-money options when constructing the implied volatility surfaces.
Three eigensurfaces are obtained for both the term structure of CDS spreads and the implied volatility surface by using the approach set forth in Da Fonseca and Gottschalk (Journal of Futures Markets 2013). The first eigensurface for each represents a majority of the respective global variance, ranging from 75% to 85%. The second eigensurface for each reflects about 10%–17% of the variance, and the third eigensurface for each reflects about 3%–5% of the variance.
The authors perform three regressions on the three credit factors, and the first credit factor is regressed on a set of volatility factors to determine cross-hedging strategies. They note the R2 of these regressions to determine the effectiveness of the hedges. Only CDS and volatility market variables are used in the regression, which differs from other papers.
Correlations matter the most during times of crisis, which is also when hedging systematic risk is most valuable. But turbulent times can lead to a breakdown in correlations and the methods used to hedge risk. I would welcome more studies that evaluate longer time periods to see how various instruments perform as hedges over business cycles.