IDEAS home Printed from https://ideas.repec.org/p/mlb/wpaper/927.html
   My bibliography  Save this paper

Computable Bounds for Extreme Event Probabilities in Stochastic Economic Models

Author

Listed:
  • John Stachurski

Abstract

The paper introduces a multiplicative drift condition for evaluating stochastic economic models. The drift condition is shown to permit computation of quantitative bounds for extreme event probabilities in terms of the model primitives. By way of illustration, the technique is applied to a simple threshold autoregression model of exchange rates.

Suggested Citation

  • John Stachurski, 2005. "Computable Bounds for Extreme Event Probabilities in Stochastic Economic Models," Department of Economics - Working Papers Series 927, The University of Melbourne.
    • Handle: RePEc:mlb:wpaper:927
    as

    Download full text from publisher

    File URL: http://www.economics.unimelb.edu.au/downloads/wpapers-05/927.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-952, July.
    2. Taylor, Alan M, 2001. "Potential Pitfalls for the Purchasing-Power-Parity Puzzle? Sampling and Specification Biases in Mean-Reversion Tests of the Law of One Price," Econometrica, Econometric Society, vol. 69(2), pages 473-498, March.
    3. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
    4. Mandelbrot, Benoit B, 1972. "Correction of an Error in "The Variation of Certain Speculative Prices" (1963)," The Journal of Business, University of Chicago Press, vol. 45(4), pages 542-543, October.
    5. 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..
    Full references (including those not matched with items on IDEAS)

    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. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    2. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, Enero-Abr.
    3. Ibrahim Chowdhury & Lucio Sarno, 2004. "Time‐Varying Volatility in the Foreign Exchange Market: New Evidence on its Persistence and on Currency Spillovers," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 759-793, June.
    4. Eric Ghysels & Andrew Harvey & Eric Renault, 1995. "Stochastic Volatility," CIRANO Working Papers 95s-49, CIRANO.
    5. Meddahi, N., 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    6. Donatien Hainaut & Franck Moraux, 2019. "A switching self-exciting jump diffusion process for stock prices," Annals of Finance, Springer, vol. 15(2), pages 267-306, June.
    7. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    8. Yueh-Neng Lin & Ken Hung, 2008. "Is Volatility Priced?," Annals of Economics and Finance, Society for AEF, vol. 9(1), pages 39-75, May.
    9. Bollerslev, Tim, 2001. "Financial econometrics: Past developments and future challenges," Journal of Econometrics, Elsevier, vol. 100(1), pages 41-51, January.
    10. Mardi Dungey & Diana Zhumabekova, 2001. "Factor analysis of a model of stock market returns using simulation-based estimation techniques," Pacific Basin Working Paper Series 2001-08, Federal Reserve Bank of San Francisco.
    11. Dinghai Xu & John Knight, 2013. "Stochastic volatility model under a discrete mixture-of-normal specification," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(2), pages 216-239, April.
    12. Paul Ormerod, 2010. "La crisis actual y la culpabilidad de la teoría macroeconómica," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 12(22), pages 111-128, January-J.
    13. Zhao, Zhibiao & Wu, Wei Biao, 2009. "Nonparametric inference of discretely sampled stable Lévy processes," Journal of Econometrics, Elsevier, vol. 153(1), pages 83-92, November.
    14. Barunik, Jozef & Vacha, Lukas, 2010. "Monte Carlo-based tail exponent estimator," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4863-4874.
    15. Dominique Guégan & Wayne Tarrant, 2012. "On the necessity of five risk measures," Annals of Finance, Springer, vol. 8(4), pages 533-552, November.
    16. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    17. Ben Klemens, 2013. "A Peer-based Model of Fat-tailed Outcomes," Papers 1304.0718, arXiv.org.
    18. Koutmos, Dimitrios, 2012. "An intertemporal capital asset pricing model with heterogeneous expectations," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(5), pages 1176-1187.
    19. Turvey, Calum G., 2001. "Random Walks And Fractal Structures In Agricultural Commodity Futures Prices," Working Papers 34151, University of Guelph, Department of Food, Agricultural and Resource Economics.
    20. Rodríguez, Mª Araceli, 2005. "Nueva Evidencia Empírica sobre las Turbulencias Cambiarias de la Peseta Española. 1989-1998/New Evidence about Turbulences on the Spanish Peseta. 1989-1998s," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 23, pages 207-230, Abril.

    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:mlb:wpaper:927. 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: Dandapani Lokanathan (email available below). General contact details of provider: https://edirc.repec.org/data/demelau.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.