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Industry-level determinants of the linkage between credit and stock markets
Journal article   Open access   Peer reviewed

Industry-level determinants of the linkage between credit and stock markets

Syed Jawad Hussain Shahzad, Román Ferrer, Shawkat Hammoudeh and Rania Jammazi
Applied economics, v 50(49), pp 5277-5301
21 Oct 2018
url
https://hdl.handle.net/10550/121988View
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Abstract

Bayesian moving average Credit default swaps credit risk stock market wavelet correlation
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.

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Domestic collaboration
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Web of Science research areas
Economics
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