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Economic links and credit spreads

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  • Gençay, Ramazan
  • Signori, Daniele
  • Xue, Yi
  • Yu, Xiao
  • Zhang, Keyi

Abstract

Counterparty risk is an important determinant of corporate credit spreads. However, there are only a few techniques available to isolate it from other factors. In this paper we describe a model of financial networks that is suitable for the construction of proxies for counterparty risk. Using data on North American supplier–customer network of public companies, we find that, for each supplier, counterparties’ leverage and option implied volatilities are significant determinants of corporate credit spreads in the period after the 2008–2009 U.S. recession. Our findings are robust after controlling for several idiosyncratic, industry, and market factors.

Suggested Citation

  • Gençay, Ramazan & Signori, Daniele & Xue, Yi & Yu, Xiao & Zhang, Keyi, 2015. "Economic links and credit spreads," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 157-169.
    • Handle: RePEc:eee:jbfina:v:55:y:2015:i:c:p:157-169
    DOI: 10.1016/j.jbankfin.2015.02.007
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    Cited by:

    1. Hollander, Hylton & Liu, Guangling, 2016. "Credit spread variability in the U.S. business cycle: The Great Moderation versus the Great Recession," Journal of Banking & Finance, Elsevier, vol. 67(C), pages 37-52.
    2. van de Leur, Michiel C.W. & Lucas, André & Seeger, Norman J., 2017. "Network, market, and book-based systemic risk rankings," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 84-90.
    3. Spatareanu, Mariana & Manole, Vlad & Kabiri, Ali & Roland, Isabelle, 2023. "Bank default risk propagation along supply chains: evidence from the U.K," LSE Research Online Documents on Economics 117351, London School of Economics and Political Science, LSE Library.
    4. Senay Agca & Volodymyr Babich & John R. Birge & Jing Wu, 2022. "Credit Shock Propagation Along Supply Chains: Evidence from the CDS Market," Management Science, INFORMS, vol. 68(9), pages 6506-6538, September.
    5. Bhanu Pratap Singh Thakur & M. Kannadhasan & Vinay Goyal, 2018. "Determinants of corporate credit spread: evidence from India," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(1), pages 59-73, March.
    6. Ali Kabiri & Vlad Malone & Isabelle Roland & Mariana Spatareanu, 2020. "Bank default risk propagation along supply chains: evidence from the UK," CEP Discussion Papers dp1699, Centre for Economic Performance, LSE.
    7. Lian, Yili, 2017. "Financial distress and customer-supplier relationships," Journal of Corporate Finance, Elsevier, vol. 43(C), pages 397-406.
    8. Tri Tri Nguyen & Manh Cuong Nguyen & Hung Quang Bui & Tuyet Nhung Vu, 2021. "The cash-holding link within the supply chain," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1309-1344, November.
    9. Mihov, Atanas & Naranjo, Andy, 2017. "Customer-base concentration and the transmission of idiosyncratic volatility along the vertical chain," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 73-100.
    10. Liang He & Shouwei Li, 2017. "Network Entropy and Systemic Risk in Dynamic Banking Systems," Complexity, Hindawi, vol. 2017, pages 1-7, November.
    11. Kabiri, Ali & Malone, Vlad & Roland, Isabelle Angeline Madeleine & Spatareanu, Mariana, 2020. "Bank default risk propagation along supply chains: evidence from the UK," LSE Research Online Documents on Economics 121832, London School of Economics and Political Science, LSE Library.
    12. Martínez, Constanza & León, Carlos, 2016. "The cost of collateralized borrowing in the Colombian money market: Does connectedness matter?," Journal of Financial Stability, Elsevier, vol. 25(C), pages 193-205.
    13. Hu, Nan & Liang, Peng & Liu, Ling & Zhu, Lu, 2022. "The bullwhip effect and credit default swap market: A study based on firm-specific bullwhip effect measure," International Review of Financial Analysis, Elsevier, vol. 84(C).
    14. Ya Qian & Wolfgang Karl Härdle & Cathy Yi-Hsuan Chen, 2017. "Industry Interdependency Dynamics in a Network Context," SFB 649 Discussion Papers SFB649DP2017-012, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    15. Berger, Theo, 2023. "Explainable artificial intelligence and economic panel data: A study on volatility spillover along the supply chains," Finance Research Letters, Elsevier, vol. 54(C).
    16. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    17. Manh Cuong Nguyen & Viet Anh Dang & Tri Tri Nguyen, 2023. "The transfer of risk taking along the supply chain," Review of Quantitative Finance and Accounting, Springer, vol. 61(4), pages 1341-1378, November.
    18. Borochin, Paul & Rush, Stephen, 2022. "Information networks in the financial sector and systemic risk," Journal of Banking & Finance, Elsevier, vol. 134(C).
    19. Mariana Spatareanu & Vlad Manole & Ali Kabiri & Isabelle Roland, 2021. "Bank Default Risk Propagation along Supply Chains: Evidence from the U.K," Working Papers Rutgers University, Newark 2021-001, Department of Economics, Rutgers University, Newark.
    20. Spatareanu, Mariana & Manole, Vlad & Kabiri, Ali & Roland, Isabelle, 2023. "Bank default risk propagation along supply chains: Evidence from the U.K," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 813-831.
    21. Spatareanu, M. & Manole, V. & Kabiri, A. & Roland, I., 2020. "Bank Default Risk Propagation along Supply Chains: Evidence from the U.K," Cambridge Working Papers in Economics 2058, Faculty of Economics, University of Cambridge.

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    More about this item

    Keywords

    NARMA; Network autoregression; Counterparty risk; Corporate credit spreads; Supply networks;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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