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Model Risk of Volatility Models

Author

Listed:
  • Lazar, Emese
  • Zhang, Ning

Abstract

A new model risk measure and estimation methodology based on loss functions is proposed in order to evaluate the accuracy of volatility models. The reliability of the proposed estimation has been verified via simulations and the estimates provide a reasonable fit to the true model risk measure. An empirical analysis based on several assets is undertaken to identify the models most affected by model risk, and concludes that the accuracy of volatility models can be improved by adjusting variance forecasts for model risk. The results indicate that after crisis situations, model risk increases especially for badly fitting volatility models.

Suggested Citation

  • Lazar, Emese & Zhang, Ning, 2025. "Model Risk of Volatility Models," Econometrics and Statistics, Elsevier, vol. 35(C), pages 1-22.
    • Handle: RePEc:eee:ecosta:v:35:y:2025:i:c:p:1-22
    DOI: 10.1016/j.ecosta.2022.06.002
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    References listed on IDEAS

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    Keywords

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    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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