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Value-at-Risk estimation with stochastic interest rate models for option-bond portfolios

Author

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  • Wang, Xiaoyu
  • Xie, Dejun
  • Jiang, Jingjing
  • Wu, Xiaoxia
  • He, Jia

Abstract

This article proposes a Monte Carlo simulation based approach for measuring Value-at-Risk of a portfolio consisting of options and bonds. The approach allows for jump-diffusions in underlying assets and affords to fit a variety of model layout, including both non-parametric and semi-parametric structures. Backtesting was conducted to assess the effectiveness of the method. The algorithm was tested against various trading positions, time horizons, and correlations between asset prices and market return rates. A prominent advantage of our approach is that its implementation does not require prior knowledge of the joint distribution or other statistical features of the related risk factors.

Suggested Citation

  • Wang, Xiaoyu & Xie, Dejun & Jiang, Jingjing & Wu, Xiaoxia & He, Jia, 2017. "Value-at-Risk estimation with stochastic interest rate models for option-bond portfolios," Finance Research Letters, Elsevier, vol. 21(C), pages 10-20.
    • Handle: RePEc:eee:finlet:v:21:y:2017:i:c:p:10-20
    DOI: 10.1016/j.frl.2016.11.013
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    References listed on IDEAS

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    Cited by:

    1. Chen, Rongda & Zhou, Hanxian & Yu, Lean & Jin, Chenglu & Zhang, Shuonan, 2021. "An efficient method for pricing foreign currency options," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    2. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    3. Dan Dobrotă & Gabriela Dobrotă & Tiberiu Dobrescu & Cristina Mohora, 2019. "The Redesigning of Tires and the Recycling Process to Maintain an Efficient Circular Economy," Sustainability, MDPI, vol. 11(19), pages 1-21, September.

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    More about this item

    Keywords

    Value-at-Risk; Monte Carlo simulation; Delta–Gamma approximation; Vasicek model; Cox–Ingersoll–Ross model;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • G1 - Financial Economics - - General Financial Markets

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