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Usos y limitaciones de los procesos estocásticos en el tratamiento de distribuciones de rendimientos con colas gordas

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  • José Carlos Ramirez Sánchez

    (ITESM y CIDE)

Abstract

This paper deals with the main theoretical problems regarding the application of stochastic processes to leptokurtic financial return distributions. A sort of statistical tests based on the stock index Banamex 30 is performed in order to choose the stochastic model that provides the best fit to the fat- tailed empirical distribution, allowing for a better return forecasting or value at risk estimate. In choosing that model the paper points out that any single set of stastistical criteria is not appropriate if it is not confronted with the risk manager's experience. Understanding the investor's aversion risk or the transaction costs involved in any trading strategy, among other elements, is very important to justify the use of any stochastic process in risk management techniques.

Suggested Citation

  • José Carlos Ramirez Sánchez, 2004. "Usos y limitaciones de los procesos estocásticos en el tratamiento de distribuciones de rendimientos con colas gordas," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 19(1), pages 51-76, June.
    • Handle: RePEc:ila:anaeco:v:19:y:2004:i:1:p:51-76
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    References listed on IDEAS

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    1. Kon, Stanley J, 1984. "Models of Stock Returns-A Comparison," Journal of Finance, American Finance Association, vol. 39(1), pages 147-165, March.
    2. Grieb, Terrance & Reyes, Mario G, 1999. "Random Walk Tests for Latin American Equity Indexes and Individual Firms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 22(4), pages 371-383, Winter.
    3. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    4. J. Doyne Farmer, 2000. "Physicists Attempt To Scale The Ivory Towers Of Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 311-333.
    5. John Y. Campbell, 2000. "Asset Pricing at the Millennium," Journal of Finance, American Finance Association, vol. 55(4), pages 1515-1567, August.
    6. Eberlein, Ernst & Keller, Ulrich & Prause, Karsten, 1998. "New Insights into Smile, Mispricing, and Value at Risk: The Hyperbolic Model," The Journal of Business, University of Chicago Press, vol. 71(3), pages 371-405, July.
    7. Richardson, Matthew & Smith, Tom, 1993. "A Test for Multivariate Normality in Stock Returns," The Journal of Business, University of Chicago Press, vol. 66(2), pages 295-321, April.
    8. Paul Glasserman & Philip Heidelberger & Perwez Shahabuddin, 2002. "Portfolio Value‐at‐Risk with Heavy‐Tailed Risk Factors," Mathematical Finance, Wiley Blackwell, vol. 12(3), pages 239-269, July.
    9. Yihong Xia, 2001. "Learning about Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation," Journal of Finance, American Finance Association, vol. 56(1), pages 205-246, February.
    10. Subu Venkataraman, 1997. "Value at risk for a mixture of normal distributions: the use of quasi- Bayesian estimation techniques," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 21(Mar), pages 2-13.
    11. Terrance Grieb & Mario G. Reyes, 1999. "Random Walk Tests For Latin American Equity Indexes And Individual Firms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 22(4), pages 371-383, December.
    12. L. C. G. Rogers, 1997. "Arbitrage with Fractional Brownian Motion," Mathematical Finance, Wiley Blackwell, vol. 7(1), pages 95-105, January.
    13. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    14. Baxter,Martin & Rennie,Andrew, 1996. "Financial Calculus," Cambridge Books, Cambridge University Press, number 9780521552899.
    15. Kim, Dongcheol & Kon, Stanley J, 1994. "Alternative Models for the Conditional Heteroscedasticity of Stock Returns," The Journal of Business, University of Chicago Press, vol. 67(4), pages 563-598, October.
    16. Hirsa, Ali & Neftci, Salih N., 2013. "An Introduction to the Mathematics of Financial Derivatives," Elsevier Monographs, Elsevier, edition 3, number 9780123846822.
    17. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    18. Nielsen, Lars Tyge, 1999. "Pricing and Hedging of Derivative Securities," OUP Catalogue, Oxford University Press, number 9780198776192.
    19. Ball, Clifford A & Torous, Walter N, 1985. "On Jumps in Common Stock Prices and Their Impact on Call Option Pricing," Journal of Finance, American Finance Association, vol. 40(1), pages 155-173, March.
    20. Ojah, Kalu & Karemera, David, 1999. "Random Walks and Market Efficiency Tests of Latin American Emerging Equity Markets: A Revisit," The Financial Review, Eastern Finance Association, vol. 34(2), pages 57-72, May.
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    More about this item

    Keywords

    stochastic process; leptokurtic financial return distribu-tions; return forecasting; value at risk estimate;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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