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Optimal hedging strategy for risk management on a network

Author

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  • Gao, Tianjiao
  • Gupta, Aparna
  • Gulpinar, Nalan
  • Zhu, Yun

Abstract

The paper develops a network-based framework to assess the impact of a firm's financial interconnections and interdependencies on it optimal hedging and risk transfer strategy. This is important consideration as risk concentrations and propagation embedded in risk transfers pose as a significant challenge for financial regulations and risk management. Using an a priori and an a posteriori analysis, we investigate the impact of the network structure on optimal hedge decisions and hedge efficacy. The a priori analysis shows that network features play an important role in determining corporate hedging decisions through their impact on hedge costs. In the a posteriori analysis for counterparty risk, benefit of modification from the a priori optimal hedge decision is realized when variance of firm value matters, but not when tail risk measures are utilized. Financial network assessment indicates that an a priori analysis is insufficient for robust hedging decisions, and choice of risk measures behind risk management objectives dictates the extent of impact of network characteristics.

Suggested Citation

  • Gao, Tianjiao & Gupta, Aparna & Gulpinar, Nalan & Zhu, Yun, 2015. "Optimal hedging strategy for risk management on a network," Journal of Financial Stability, Elsevier, vol. 16(C), pages 31-44.
  • Handle: RePEc:eee:finsta:v:16:y:2015:i:c:p:31-44
    DOI: 10.1016/j.jfs.2014.10.005
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    References listed on IDEAS

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    Cited by:

    1. repec:eee:intfin:v:58:y:2019:i:c:p:78-95 is not listed on IDEAS
    2. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

    More about this item

    Keywords

    Risk management; Hedging decisions; Financial network; Optimal hedging strategy;

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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