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Financial derivatives and bank risk: evidence from eighteen developed markets

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  • Xing Huan
  • Antonio Parbonetti

Abstract

We examine the relationship between equity risk and the use of financial derivatives with a sample of 555 banks from eighteen developed markets from 2006 to 2015. Our main findings suggest that banks’ use of financial derivatives increased their risk. This increase in risk can be driven by banks’ use of derivatives for speculative purposes, by suboptimal hedging to obtain hedge accounting status, or from accounting mismatches that generate volatility in earnings. We also show that this relationship is nonlinear. Too-Big-To-Fail banks and those that employ a traditional retail banking business model are subject to lower idiosyncratic risk. We address endogeneity concerns using instrumental variables capturing the use of derivatives with portfolio ranking. Overall, our study contributes to understanding the impact of derivatives use on bank risk and the risk consequences of a bank’s business model choice.

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  • Xing Huan & Antonio Parbonetti, 2019. "Financial derivatives and bank risk: evidence from eighteen developed markets," Accounting and Business Research, Taylor & Francis Journals, vol. 49(7), pages 847-874, November.
    • Handle: RePEc:taf:acctbr:v:49:y:2019:i:7:p:847-874
    DOI: 10.1080/00014788.2019.1618695
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    Cited by:

    1. Zamzamir, Zaminor & Haron, Razali & Baharul Ulum, Zatul Karamah Ahmad & Abdullah Othman, Anwar Hasan, 2021. "Non-linear relationship between foreign currency derivatives and firm value: evidence on Sharī‘ah compliant firms," Islamic Economic Studies, The Islamic Research and Training Institute (IRTI), vol. 28, pages 156-173.
    2. Bales, Stephan & Burghartz, Kaspar & Burghof, Hans-Peter & Hitz, Lukas, 2023. "Does the source of uncertainty matter? The impact of financial, newspaper and Twitter-based measures on U.S. banks," Research in International Business and Finance, Elsevier, vol. 65(C).
    3. Zheng Gong & Carmine Ventre & John O'Hara, 2021. "The Efficient Hedging Frontier with Deep Neural Networks," Papers 2104.05280, arXiv.org.

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