IDEAS home Printed from https://ideas.repec.org/a/bla/ecnote/v30y2001i2p167-181.html
   My bibliography  Save this article

Non parametric VaR Techniques. Myths and Realities

Author

Listed:
  • Giovanni Barone-Adesi
  • Kostas Giannopoulos

Abstract

type="main" xml:lang="en"> VaR (value-at-risk) estimates are currently based on two main techniques: the variance-covariance approach or simulation. Statistical and computational problems affect the reliability of these techniques. We illustrate a new technique – filtered historical simulation (FHS) – designed to remedy some of the shortcomings of the simulation approach. We compare the estimates it produces with traditional bootstrapping estimates. (J.E.L.: G19).

Suggested Citation

  • Giovanni Barone-Adesi & Kostas Giannopoulos, 2001. "Non parametric VaR Techniques. Myths and Realities," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 30(2), pages 167-181, July.
    • Handle: RePEc:bla:ecnote:v:30:y:2001:i:2:p:167-181
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.0391-5026.2001.00052.x
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Nieto, María Rosa & Ruiz Ortega, Esther, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Escanciano, Juan Carlos & Pei, Pei, 2012. "Pitfalls in backtesting Historical Simulation VaR models," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2233-2244.
    3. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
    4. Agnieszka Surowiec & Tomasz Warowny, 2021. "Covid-19 Death Risk Estimation Using VaR Method," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 368-379.
    5. Shaozhen Chen & Bangqian Zhang & Jinjin Deng, 2018. "Research on Risk Measurement in Financial Market Based on GARCH-VaR and FHS¡ª¡ªAn Example of Chinese Bond Market," Applied Economics and Finance, Redfame publishing, vol. 5(4), pages 102-116, July.
    6. Marimoutou, Velayoudoum & Raggad, Bechir & Trabelsi, Abdelwahed, 2009. "Extreme Value Theory and Value at Risk: Application to oil market," Energy Economics, Elsevier, vol. 31(4), pages 519-530, July.
    7. Emrah Altun & Huseyin Tatlidil & Gamze Ozel & Saralees Nadarajah, 2018. "Does the Assumption on Innovation Process Play an Important Role for Filtered Historical Simulation Model?," JRFM, MDPI, vol. 11(1), pages 1-13, January.
    8. Timotheos Angelidis & Alexandros Benos, 2008. "Value-at-Risk for Greek Stocks," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 67-104, March-Jun.
    9. Chlebus Marcin, 2017. "EWS-GARCH: New Regime Switching Approach to Forecast Value-at-Risk," Central European Economic Journal, Sciendo, vol. 3(50), pages 01-25, December.
    10. Samuel N. Cohen & Christoph Reisinger & Sheng Wang, 2022. "Estimating risks of option books using neural-SDE market models," Papers 2202.07148, arXiv.org.
    11. Nikola RADIVOJEVIĆ & Luka FILIPOVI & Тomislav D. BRZAKOVIĆ, 2020. "A New Semiparametric Mirrored Historical Simulation Value-At-Risk Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-21, March.
    12. Wang, Guochang & Zhu, Ke & Li, Guodong & Li, Wai Keung, 2022. "Hybrid quantile estimation for asymmetric power GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 264-284.
    13. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    14. Francesco Paolo Natale, 2008. "Optimisation in the presence of tail-dependence and tail risk: A heuristic approach for strategic asset allocation," Journal of Asset Management, Palgrave Macmillan, vol. 8(6), pages 374-400, February.
    15. Chen, Fen-Ying & Liao, Szu-Lang, 2009. "Modelling VaR for foreign-asset portfolios in continuous time," Economic Modelling, Elsevier, vol. 26(1), pages 234-240, January.
    16. Guochang Wang & Ke Zhu & Guodong Li & Wai Keung Li, 2019. "Hybrid quantile estimation for asymmetric power GARCH models," Papers 1911.09343, arXiv.org.
    17. Giannopoulos, Kostas & Tunaru, Radu, 2005. "Coherent risk measures under filtered historical simulation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 979-996, April.
    18. Bagher Adabi & Mohsen Mehrara & Shapour Mohammadi, 2015. "Evaluation Approaches of Value at Risk for Tehran Stock Exchange," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(1), pages 41-62, Winter.
    19. Claude Martini & Arianna Mingone, 2023. "A closed form model-free approximation for the Initial Margin of option portfolios," Papers 2306.16346, arXiv.org.
    20. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.

    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:ecnote:v:30:y:2001:i:2:p:167-181. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: http://www.blackwellpublishing.com/journal.asp?ref=0391-5026 .

    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.