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Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator

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  • Dilip Kumar

    (Indian Institute of Management Kashipur)

Abstract

We provide a framework based on the unbiased extreme value volatility estimator to predict long and short position value-at-risk (VaR). The given framework incorporates the impact of asymmetry, structural breaks and fat tails in volatility. We generate forecasts of long and short position VaR for the cases when future structural breaks are known as well as unknown. We evaluate its VaR forecasting performance using various backtesting approaches for both long and short positions and compare the results with that from return based models. Our findings indicate that incorporating the impact of structural breaks in volatility indeed improves the accuracy of VaR forecasts of the proposed framework.

Suggested Citation

  • Dilip Kumar, 2020. "Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 587-610, September.
    • Handle: RePEc:spr:jqecon:v:18:y:2020:i:3:d:10.1007_s40953-020-00197-w
    DOI: 10.1007/s40953-020-00197-w
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    More about this item

    Keywords

    Extreme value volatility estimator; Structural breaks; Value-at-risk; Asymmetry; Risk management;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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