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Measuring Equity Volatility: the case of Chilean Stock Index

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  • Rodrigo 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 suggested in Parkinson (1980), Garman and Klass (1980), and Rogers and Satchell (1991). Those measurements use additional information of prices throughout the day, which makes them more efficient than the traditional ones. We consider this property relevant for financial stress episodies, when traditional measurements fail. In an empirical application for the Chilean stock market, we confirm the theoretical results and provide an index of price volatility based on daily highs and lows.

Suggested Citation

  • Rodrigo Alfaro & Carmen Gloria Silva, 2008. "Measuring Equity Volatility: the case of Chilean Stock Index," Working Papers Central Bank of Chile 462, Central Bank of Chile.
  • Handle: RePEc:chb:bcchwp:462
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    References listed on IDEAS

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    1. 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.
    2. Soosung Hwang & Pedro L. Valls Pereira, 2006. "Small sample properties of GARCH estimates and persistence," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 473-494.
    3. Linton, Oliver, 1997. "An Asymptotic Expansion in the GARCH(l, 1) Model," Econometric Theory, Cambridge University Press, vol. 13(04), pages 558-581, August.
    4. 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.
    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. Lumsdaine, Robin L, 1995. "Finite-Sample Properties of the Maximum Likelihood Estimator in GARCH(1,1) and IGARCH(1,1) Models: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 1-10, January.
    7. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    8. Robert F. Engle & David F. Hendry & David Trumble, 1985. "Small-Sample Properties of ARCH Estimators and Tests," Canadian Journal of Economics, Canadian Economics Association, vol. 18(1), pages 66-93, February.
    9. 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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