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Long-run relationships between US financial credit markets and risk factors: Evidence from the quantile ARDL approach
Journal article   Peer reviewed

Long-run relationships between US financial credit markets and risk factors: Evidence from the quantile ARDL approach

Walid Mensi, Syed Jawad Hussain Shahzad, Shawkat Hammoudeh, Besma Hkiri and Khamis Hamed Al Yahyaee
Finance research letters, v 29
Jun 2019

Abstract

Financial credit sectors Quantile ARDL model Risk factors
•We examine the impact of oil, VIX and federal funds rate on US financial credit markets.•We use the quantile ARDL model to account for the impacts under different distributions.•The federal funds rate and the VIX increase the credit risk of the financial sector when the credit risk is on a rising trend.•Oil prices, and to a lesser extent, decrease the credit risk.•The short- and long-run impacts of the risk factors are time-varying and heterogeneous across the different credit market states. This paper examines the quantile-dependent short- and long-run impact of the FFR, VIX index and crude oil prices on the credit risk of the U.S. banking, financial services and insurance sectors. Using the quantile autoregressive distributed lag model, we find that the federal funds rate and the equity volatility mainly increase the credit risk of the financial sector when the credit risk is on a rising trend. However, oil prices, and to a lesser extent, decrease the credit risk. The short- and long-run impacts of the considered risk factors are time-varying and heterogeneous across the different credit market states.

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51 citations in Scopus

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Collaboration types
Domestic collaboration
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Web of Science research areas
Business, Finance
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