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Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment

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  • Berger, Theo
  • Gençay, Ramazan

Abstract

In this paper, we present a novel perspective on data filtering and present an innovative wavelet-based approach that leads to improved Value-at-Risk (VaR) forecasts. A separation of financial conditional volatility into short-, mid- and long-run components allows us to study the relevance of these frequency components with respect to a regulatory quality assessment for daily VaR forecasts.

Suggested Citation

  • Berger, Theo & Gençay, Ramazan, 2018. "Improving daily Value-at-Risk forecasts: The relevance of short-run volatility for regulatory quality assessment," Journal of Economic Dynamics and Control, Elsevier, vol. 92(C), pages 30-46.
    • Handle: RePEc:eee:dyncon:v:92:y:2018:i:c:p:30-46
    DOI: 10.1016/j.jedc.2018.03.016
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    Cited by:

    1. George Tzagkarakis & Frantz Maurer, 2020. "An energy-based measure for long-run horizon risk quantification," Annals of Operations Research, Springer, vol. 289(2), pages 363-390, June.
    2. Amaro, Raphael & Pinho, Carlos & Madaleno, Mara, 2022. "Forecasting the Value-at-Risk of energy commodities: A comparison of models and alternative distribution functions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 77-101.
    3. He, Kaijian & Tso, Geoffrey K.F. & Zou, Yingchao & Liu, Jia, 2018. "Crude oil risk forecasting: New evidence from multiscale analysis approach," Energy Economics, Elsevier, vol. 76(C), pages 574-583.
    4. Zhang, Xu & Yang, Xian & He, Qizhi, 2022. "Multi-scale systemic risk and spillover networks of commodity markets in the bullish and bearish regimes," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    5. Czudaj, Robert L., 2019. "Crude oil futures trading and uncertainty," Energy Economics, Elsevier, vol. 80(C), pages 793-811.
    6. Berger, Theo & Czudaj, Robert L., 2020. "Commodity futures and a wavelet-based risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    7. Bu, Di & Liao, Yin & Shi, Jing & Peng, Hongfeng, 2019. "Dynamic expected shortfall: A spectral decomposition of tail risk across time horizons," Journal of Economic Dynamics and Control, Elsevier, vol. 108(C).
    8. Yahya, Muhammad & Oglend, Atle & Dahl, Roy Endré, 2019. "Temporal and spectral dependence between crude oil and agricultural commodities: A wavelet-based copula approach," Energy Economics, Elsevier, vol. 80(C), pages 277-296.

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    More about this item

    Keywords

    Value-at-Risk; Forecasting; Wavelet decomposition; Regulatory back-testing;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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