Industry-level determinants of the linkage between credit and stock markets. Issue 49 (21st October 2018)

• Record Type: Journal Article
• Authors: Shahzad, Syed Jawad Hussain; Ferrer, Román; Hammoudeh, Shawkat; Jammazi, Rania
• Is Part Of: Applied economics. Volume 50:Issue 49(2018)
• Page Start: 5277
• Page End: 5301
• Publication Date: 2018-10-21
• Subjects: Credit default swaps -- credit risk -- stock market -- wavelet correlation -- Bayesian moving average; C20 -- C31 -- E44 -- G11; Economics -- Periodicals; 330
• DOI: 10.1080/00036846.2018.1486986
• Languages: English
• ISSNs: 0003-6846

Abstract

ABSTRACT: This paper examines the relationship between US credit default swaps (CDS) and stock returns on an industry-wide basis across a number of investment horizons, with particular focus on the major determinants of such a relationship. Wavelet analysis is first applied to extract the CDS–stock wavelet correlation for each US industry. Then, Bayesian Model Averaging is employed to identify the key driving factors of the industry CDS–stock wavelet correlations at short- and long-term horizons. The empirical results indicate that the wavelet correlations between the industry CDS and stock returns are primarily negative over time and across time scales. Moreover, the CDS–stock correlation at longer horizons exhibits a much more stable pattern than its counterpart at shorter time frames. The results also demonstrate that the volatility of US Treasury and stock markets, as measured by the MOVE and VIX indices, respectively, the volatility of volatility, as captured by the VVIX index, and US economic policy uncertainty, as measured by the EPU index, are the most robust determinants of the correlation between CDS and stock returns at shorter and longer horizons for most US industries. In contrast, the Fama–French systematic equity factors exhibit a practically negligible explanatory power on the CDS–stock link.