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Increasing the risk management effectiveness from higher accuracy: A novel non-parametric method

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  • Huang, Jinbo
  • Ding, Ashley
  • Li, Yong
  • Lu, Dong

Abstract

The importance of effective risk management has never been greater in recent decades. However, the estimate accuracy of risk measures, such as Value-at-Risk, remains a challenge. In this paper, we propose a novel non-parametric method to efficiently enhance the accuracy of risk estimation as our method can avoid model misspecification and fully explore the tail information contained in asset returns. The non-parametric Value-at-Risk measure is embedded into a risk hedge model to increase the effectiveness of risk management. Simulations show that our new method outperforms existing methods in terms of accuracy. Empirical findings support that the improved estimation is helpful for more effectively managing risk in weather-sensitive markets.

Suggested Citation

  • Huang, Jinbo & Ding, Ashley & Li, Yong & Lu, Dong, 2020. "Increasing the risk management effectiveness from higher accuracy: A novel non-parametric method," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
  • Handle: RePEc:eee:pacfin:v:62:y:2020:i:c:s0927538x20300263
    DOI: 10.1016/j.pacfin.2020.101373
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    Cited by:

    1. Cornwell, Nikki & Bilson, Christopher & Gepp, Adrian & Stern, Steven & Vanstone, Bruce J., 2023. "Modernising operational risk management in financial institutions via data-driven causal factors analysis: A pre-registered report," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    2. Hao Lu & Jie Bao, 2022. "Spatial Differentiation Effect of Rural Logistics in Urban Agglomerations in China Based on the Fuzzy Neural Network," Sustainability, MDPI, vol. 14(15), pages 1-23, July.
    3. Cornwell, Nikki & Bilson, Christopher & Gepp, Adrian & Stern, Steven & Vanstone, Bruce J., 2023. "Modernising operational risk management in financial institutions via data-driven causal factors analysis: A pre-registered study," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).

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    More about this item

    Keywords

    Risk hedge; Value-at-Risk; Non-parametric estimation; Weather-sensitive markets;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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