Modelling the asymmetry of stock market volatility

Ólan T. Henry

59 citations0/0 files storedApplied Financial Economics

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Financial Risk and Volatility Modeling Financial Markets and Investment Strategies Market Dynamics and Volatility

Abstract

Recent studies suggest that a negative shock to stock prices will generate more volatility than a positive shock of equal magnitude. This paper uses daily data from the Hong Kong Stock Exchange to illustrate the nature of stock market volatility. Regression-based tests for integration in variance are applied, providing contrasting results to the usual test based on the Wald statistic. A partially non-parametric model of the relationship between news and volatility is estimated and used in conjunction with tests for the sensitivity to both the size and sign of a shock as a metric to judge various candidate characterizations of the underlying data generating process.

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1988Testing for a Unit Root in Time Series Regression 1981Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root 1991Conditional Heteroskedasticity in Asset Returns: A New Approach 1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks 1992ARCH modeling in finance 1993Measuring and Testing the Impact of News on Volatility

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