IDEAS home Printed from https://ideas.repec.org/a/fip/fedbne/y1997inovp17-28.html
   My bibliography  Save this article

Model error

Author

Listed:
  • Katerina Simons

Abstract

Modern finance would not have been possible without models. Increasingly complex quantitative models drive financial innovation and the growth of derivatives markets. Models are necessary to value financial instruments and to measure the risks of individual positions and portfolios. Yet when used inappropriately, the models themselves can become an important source of risk. Recently, several well-publicized instances occurred of institutions suffering significant losses attributed to model error. This has sharpened the interest in model risk among financial institutions and their regulators.> This article describes various models and discusses model errors characteristic of two types -- valuation models for individual securities, and models of market risk. It also reviews a number of practical issues related to model development and describes the approach taken by bank regulators to model risk. The author points out that a trade-off almost always exists between the realism and the analytical tractability of a model. Striking the right balance in the face of this trade-off, she writes, and maintaining it through changing market conditions for different financial instruments, is more art than science and requires considerable experience and judgment.

Suggested Citation

  • Katerina Simons, 1997. "Model error," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 17-28.
  • Handle: RePEc:fip:fedbne:y:1997:i:nov:p:17-28
    as

    Download full text from publisher

    File URL: http://www.bostonfed.org/economic/neer/neer1997/neer697b.htm
    Download Restriction: no

    File URL: http://www.bostonfed.org/economic/neer/neer1997/neer697b.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    3. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    4. Krugman, Paul, 1979. "A Model of Balance-of-Payments Crises," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 11(3), pages 311-325, August.
    5. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    6. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. 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.
    2. Carol Alexander & Jose Maria Sarabia, 2010. "Endogenizing Model Risk to Quantile Estimates," ICMA Centre Discussion Papers in Finance icma-dp2010-07, Henley Business School, University of Reading.
    3. Katerina Simons, 2000. "Use of value at risk by institutional investors," New England Economic Review, Federal Reserve Bank of Boston, issue Nov, pages 21-30.
    4. Kato, Toshiyasu & Yoshiba, Toshinao, 2000. "Model Risk and Its Control," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 18(2), pages 129-157, December.
    5. Chung, Huimin & Lee, Chin-Shen & Wu, Soushan, 2002. "The effects of model errors and market imperfections on financial institutions writing derivative warrants: Simulation evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 10(1), pages 55-75, January.
    6. Ralph C. Kimball, 2000. "Failures in risk management," New England Economic Review, Federal Reserve Bank of Boston, issue Jan, pages 3-12.
    7. Daniela MATEI & Dragos CRISTEA & Alexandru CAPATINA, 2012. "Risk Management in the Age of Turbulence - Failures and Challenges," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 17-22.

    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. Pierdzioch, Christian, 2000. "Noise Traders? Trigger Rates, FX Options, and Smiles," Kiel Working Papers 970, Kiel Institute for the World Economy (IfW Kiel).
    2. David Edelman & Thomas Gillespie, 2000. "The Stochastically Subordinated Poisson Normal Process for Modelling Financial Assets," Annals of Operations Research, Springer, vol. 100(1), pages 133-164, December.
    3. Ghysels, E. & Harvey, A. & Renault, E., 1995. "Stochastic Volatility," Papers 95.400, Toulouse - GREMAQ.
    4. Kaehler, Jürgen & Marnet, Volker, 1993. "Markov-switching models for exchange-rate dynamics and the pricing of foreign-currency options," ZEW Discussion Papers 93-03, ZEW - Leibniz Centre for European Economic Research.
    5. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    6. Chuang, Wen-I & Huang, Teng-Ching & Lin, Bing-Huei, 2013. "Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 168-187.
    7. Ata Türkoğlu, 2016. "Normally distributed high-frequency returns: a subordination approach," Quantitative Finance, Taylor & Francis Journals, vol. 16(3), pages 389-409, March.
    8. Bauer, Rob M M J & Nieuwland, Frederick G M C & Verschoor, Willem F C, 1994. "German Stock Market Dynamics," Empirical Economics, Springer, vol. 19(3), pages 397-418.
    9. Giulia Di Nunno & Kęstutis Kubilius & Yuliya Mishura & Anton Yurchenko-Tytarenko, 2023. "From Constant to Rough: A Survey of Continuous Volatility Modeling," Mathematics, MDPI, vol. 11(19), pages 1-35, October.
    10. Shi, Leilei, 2006. "Does security transaction volume–price behavior resemble a probability wave?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 419-436.
    11. Chihwa Kao, 2001. "Some New Approaches to Formulate and Estimate Friction-Bernoulli Jump Diffusion and Friction-GARCH," Center for Policy Research Working Papers 35, Center for Policy Research, Maxwell School, Syracuse University.
    12. Ncube, Mthuli, 1996. "Modelling implied volatility with OLS and panel data models," Journal of Banking & Finance, Elsevier, vol. 20(1), pages 71-84, January.
    13. Wild, Phillip & Hinich, Melvin J. & Foster, John, 2010. "Are daily and weekly load and spot price dynamics in Australia's National Electricity Market governed by episodic nonlinearity?," Energy Economics, Elsevier, vol. 32(5), pages 1082-1091, September.
    14. Jean -Luc Prigent & Olivier Renault & Olivier Scaillet, 1999. "An Autoregressive Conditional Binomial Option Pricing Model," Working Papers 99-65, Center for Research in Economics and Statistics.
    15. Ivivi Joseph Mwaniki, 2019. "Modeling heteroscedastic, skewed and leptokurtic returns in discrete time," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(5), pages 1-1.
    16. Gurdip Bakshi & Liuren Wu, 2010. "The Behavior of Risk and Market Prices of Risk Over the Nasdaq Bubble Period," Management Science, INFORMS, vol. 56(12), pages 2251-2264, December.
    17. Peter A. Abken & Saikat Nandi, 1996. "Options and volatility," Economic Review, Federal Reserve Bank of Atlanta, vol. 81(Dec), pages 21-35.
    18. He, Xue-Zhong & Li, Youwei, 2015. "Testing of a market fraction model and power-law behaviour in the DAX 30," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 1-17.
    19. Eom, Cheoljun & Kaizoji, Taisei & Scalas, Enrico, 2019. "Fat tails in financial return distributions revisited: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    20. Giacomo Bormetti & Sofia Cazzaniga, 2014. "Multiplicative noise, fast convolution and pricing," Quantitative Finance, Taylor & Francis Journals, vol. 14(3), pages 481-494, March.

    More about this item

    Keywords

    Econometric models;

    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:fip:fedbne:y:1997:i:nov:p:17-28. 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: Catherine Spozio (email available below). General contact details of provider: https://edirc.repec.org/data/frbbous.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.