IDEAS home Printed from https://ideas.repec.org/a/bla/finrev/v59y2024i2p519-543.html

Good risk measures, bad statistical assumptions, ugly risk forecasts

Author

Listed:
  • Michael Michaelides
  • Niraj Poudyal

Abstract

This paper proposes the time‐heterogeneous Student's t autoregressive model as an alternative to the various volatility forecast models documented in the literature. The empirical results indicate that: (i) the proposed model has better forecasting performance than other commonly used models, and (ii) the problem of reliable risk measurement arises primarily from the model risk associated with risk forecast models rather than the particular risk measure for computing risk. Based on the results, the paper makes recommendations to regulators and practitioners.

Suggested Citation

  • Michael Michaelides & Niraj Poudyal, 2024. "Good risk measures, bad statistical assumptions, ugly risk forecasts," The Financial Review, Eastern Finance Association, vol. 59(2), pages 519-543, May.
    • Handle: RePEc:bla:finrev:v:59:y:2024:i:2:p:519-543
    DOI: 10.1111/fire.12368
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/fire.12368
    Download Restriction: no
    File URL: https://libkey.io/10.1111/fire.12368?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Berger, Allen N. & Bouwman, Christa H.S., 2013. "How does capital affect bank performance during financial crises?," Journal of Financial Economics, Elsevier, vol. 109(1), pages 146-176.
    2. Boucher, Christophe M. & Daníelsson, Jón & Kouontchou, Patrick S. & Maillet, Bertrand B., 2014. "Risk models-at-risk," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 72-92.
    3. repec:hal:journl:hal-02312332 is not listed on IDEAS
    4. Gneiting, Tilmann, 2011. "Making and Evaluating Point Forecasts," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 746-762.
    5. Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
    6. Laeven, Luc & Ratnovski, Lev & Tong, Hui, 2016. "Bank size, capital, and systemic risk: Some international evidence," Journal of Banking & Finance, Elsevier, vol. 69(S1), pages 25-34.
    7. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    8. Mohammad Bitar & Wadad Saad & Mohammed Benlemlih, 2016. "Bank Risk and Performance in the MENA Region: The Importance of Capital Requirements," Post-Print halshs-01321636, HAL.
    9. Michaelides, Michael & Spanos, Aris, 2020. "On modeling heterogeneity in linear models using trend polynomials," Economic Modelling, Elsevier, vol. 85(C), pages 74-86.
    10. Johanna F. Ziegel, 2016. "Coherence And Elicitability," Mathematical Finance, Wiley Blackwell, vol. 26(4), pages 901-918, October.
    11. Spanos, Aris, 1994. "On Modeling Heteroskedasticity: The Student's t and Elliptical Linear Regression Models," Econometric Theory, Cambridge University Press, vol. 10(2), pages 286-315, June.
    12. Daníelsson, Jón & Jorgensen, Bjørn N. & Samorodnitsky, Gennady & Sarma, Mandira & de Vries, Casper G., 2013. "Fat tails, VaR and subadditivity," Journal of Econometrics, Elsevier, vol. 172(2), pages 283-291.
    13. Maasoumi, Esfandiar & Zaman, Asad & Ahmed, Mumtaz, 2010. "Tests for structural change, aggregation, and homogeneity," Economic Modelling, Elsevier, vol. 27(6), pages 1382-1391, November.
    14. Kellner, Ralf & Rösch, Daniel, 2016. "Quantifying market risk with Value-at-Risk or Expected Shortfall? – Consequences for capital requirements and model risk," Journal of Economic Dynamics and Control, Elsevier, vol. 68(C), pages 45-63.
    15. Susanne Emmer & Marie Kratz & Dirk Tasche, . "What is the best risk measure in practice? A comparison of standard measures," Journal of Risk, Journal of Risk.
    16. Danielsson, Jon, 2002. "The emperor has no clothes: Limits to risk modelling," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1273-1296, July.
    17. HENDRY, David F. & RICHARD, Jean-François, 1983. "The econometric analysis of economic time series," LIDAM Reprints CORE 531, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Rafael Repullo & Javier Suarez, 2013. "The Procyclical Effects of Bank Capital Regulation," The Review of Financial Studies, Society for Financial Studies, vol. 26(2), pages 452-490.
    19. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    20. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    21. Bitar, Mohammad & Saad, Wadad & Benlemlih, Mohammed, 2016. "Bank risk and performance in the MENA region: The importance of capital requirements," Economic Systems, Elsevier, vol. 40(3), pages 398-421.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Niall O’Donnell & Darren Shannon & Barry Sheehan & Badar Nadeem Ashraf, 2024. "The Impact of COVID-19 on the Fama-French Five-Factor Model: Unmasking Industry Dynamics," IJFS, MDPI, vol. 12(4), pages 1-31, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James Ming Chen, 2018. "On Exactitude in Financial Regulation: Value-at-Risk, Expected Shortfall, and Expectiles," Risks, MDPI, vol. 6(2), pages 1-28, June.
    2. Mohammed Berkhouch & Fernanda Maria Müller & Ghizlane Lakhnati & Marcelo Brutti Righi, 2022. "Deviation-Based Model Risk Measures," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 527-547, February.
    3. Farkas, Walter & Fringuellotti, Fulvia & Tunaru, Radu, 2020. "A cost-benefit analysis of capital requirements adjusted for model risk," Journal of Corporate Finance, Elsevier, vol. 65(C).
    4. Lazar, Emese & Zhang, Ning, 2025. "Model Risk of Volatility Models," Econometrics and Statistics, Elsevier, vol. 35(C), pages 1-22.
    5. Righi, Marcelo Brutti & Müller, Fernanda Maria & Moresco, Marlon Ruoso, 2020. "On a robust risk measurement approach for capital determination errors minimization," Insurance: Mathematics and Economics, Elsevier, vol. 95(C), pages 199-211.
    6. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Risk quantification for commodity ETFs: Backtesting value-at-risk and expected shortfall," International Review of Financial Analysis, Elsevier, vol. 70(C).
    7. Pitera, Marcin & Schmidt, Thorsten, 2018. "Unbiased estimation of risk," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 133-145.
    8. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524.
    9. Weiqing Wang & Shuhao Liang & Liukai Wang & Yu Xiong, 2025. "Mixed frequency data and portfolio selection: A novel approach integrating DEA with mixed frequency data sources," Annals of Operations Research, Springer, vol. 347(3), pages 1533-1565, April.
    10. Kouzez, Marc, 2023. "Political environment and bank performance: Does bank size matter?," Economic Systems, Elsevier, vol. 47(1).
    11. Marcelo Brutti Righi, 2018. "A theory for combinations of risk measures," Papers 1807.01977, arXiv.org, revised May 2023.
    12. Enilov, Martin & Mensi, Walid & Stankov, Petar, 2023. "Does safe haven exist? Tail risks of commodity markets during COVID-19 pandemic," Journal of Commodity Markets, Elsevier, vol. 29(C).
    13. Fissler Tobias & Ziegel Johanna F., 2021. "On the elicitability of range value at risk," Statistics & Risk Modeling, De Gruyter, vol. 38(1-2), pages 25-46, January.
    14. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2021. "Regulation of bank proprietary trading post 2007–09 crisis: An examination of the Basel framework and Volcker rule," Journal of International Money and Finance, Elsevier, vol. 119(C).
    15. Marie Kratz & Yen H Lok & Alexander J Mcneil, 2016. "Multinomial var backtests: A simple implicit approach to backtesting expected shortfall," Working Papers hal-01424279, HAL.
    16. Paul Embrechts & Tiantian Mao & Qiuqi Wang & Ruodu Wang, 2021. "Bayes risk, elicitability, and the Expected Shortfall," Mathematical Finance, Wiley Blackwell, vol. 31(4), pages 1190-1217, October.
    17. Le, Trung H., 2020. "Forecasting value at risk and expected shortfall with mixed data sampling," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1362-1379.
    18. Bingzhen Geng & Yang Liu & Yimiao Zhao, 2024. "Value-at-Risk- and Expectile-based Systemic Risk Measures and Second-order Asymptotics: With Applications to Diversification," Papers 2404.18029, arXiv.org.
    19. Ruodu Wang & Ričardas Zitikis, 2021. "An Axiomatic Foundation for the Expected Shortfall," Management Science, INFORMS, vol. 67(3), pages 1413-1429, March.
    20. Xia Han & Liyuan Lin & Ruodu Wang, 2023. "Diversification quotients based on VaR and ES," Papers 2301.03517, arXiv.org, revised May 2023.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:finrev:v:59:y:2024:i:2:p:519-543. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/efaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.