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Size does matter. A study on the required window size for optimal quality market risk models

Author

Listed:
  • Mateusz Buczyński

    (Interdisciplinary Doctoral School, University of Warsaw)

  • Marcin Chlebus

    (Faculty of Economic Sciences, University of Warsaw)

Abstract

When it comes to market risk models, should we use full data that we possess or rather find a sufficient subsample? We have conducted a study of different fixed moving window’s lengths (from 300 to 2000 observations) for three Value-at-Risk models: historical simulation, GARCH and CAViaR model for three different indexes: WIG20, S&P500 and FTSE100. Testing samples contained 250 observations, each ending with the end of years 2015-2019. We have also addressed the subjectivity of choosing the window’s size by testing change points detection algorithms: binary segmentation and Pelt; to find the best matching cut-off point. Results indicate that the size of the training sample greater than 900-1000 observations doesn’t increase the quality of the model, while the lengths lower than such cut-off provide unsatisfactory results and decrease model’s conservatism. Change point detection methods provide more accurate models. Applying the algorithms with every model’s recalculation provides results better by on average 1 exceedance. Our recommendation is to use GARCH or CAViaR model with recalculated window size.

Suggested Citation

  • Mateusz Buczyński & Marcin Chlebus, 2020. "Size does matter. A study on the required window size for optimal quality market risk models," Working Papers 2020-09, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2020-09
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    File URL: https://www.wne.uw.edu.pl/index.php/download_file/5577/
    File Function: First version, 2020
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    More about this item

    Keywords

    Value at Risk; historical simulation; CAViaR; GARCH; forecast comparison; sample size;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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