Measuring Equity Volatility: the case of Chilean Stock Index
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.
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- 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.
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- 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.
- 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.
- 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.
- 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)
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