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Volatilidad de Indices Accionarios: El caso del IPSA

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  • Rodrigo A. Alfaro
  • Carmen Gloria Silva

Abstract

This paper reviews the traditional ways to measure volatility which are based only on closing prices, and introduces alternative measurements that use additional information of prices during the day: opening, minimum, maximum, and closing prices. Using th

Suggested Citation

  • Rodrigo A. Alfaro & Carmen Gloria Silva, 2008. "Volatilidad de Indices Accionarios: El caso del IPSA," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 45(132), pages 217-233.
    • Handle: RePEc:ioe:cuadec:v:45:y:2008:i:132:p:217-233
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    File URL: http://www.economia.uc.cl/docs/132alfaa.pdf
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    References listed on IDEAS

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    1. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    2. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    3. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    4. Hwang. S. & Pedro L. Valls Pereira, 2003. "Small Sample Properties of GARCH Estimates and Persistence," Finance Lab Working Papers flwp_48, Finance Lab, Insper Instituto de Ensino e Pesquisa.
    5. Yang, Dennis & Zhang, Qiang, 2000. "Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices," The Journal of Business, University of Chicago Press, vol. 73(3), pages 477-491, July.
    6. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. 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.
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    Citations

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    Cited by:

    1. Dale F. Gray & Carlos J. García & Leonardo Luna & Jorge E. Restrepo, 2011. "Incorporating Financial Sector Risk Into Monetary Policy Models: Application to Chile," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Alfaro (ed.),Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 6, pages 159-197, Central Bank of Chile.
    2. Contreras-Reyes, Javier E. & Jeldes-Delgado, Fabiola & Carrasco, Raúl, 2024. "Jensen-Detrended Cross-Correlation function for non-stationary time series with application to Latin American stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 654(C).
    3. Alfaro, Rodrigo & Silva, Carmen Gloria, 2010. "Stock Index Volatility: the case of IPSA," MPRA Paper 25906, University Library of Munich, Germany, revised 31 Mar 2010.
    4. Rodrigo A. Alfaro. & Andrés Sagner & Carmen G. Silva, 2011. "Aplicaciones del Modelo Binomial para el Análisis de Riesgo," Working Papers Central Bank of Chile 631, Central Bank of Chile.

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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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