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Predictive ability of low-frequency volatility measures: Evidence from the Hong Kong stock markets

Christopher Gan, Gilbert Nartea () and Wu, Ji (George)

Finance Research Letters, 2018, vol. 26, issue C, 40-46

Abstract: We employ low-frequency data to estimate historical volatility measures for Hong Kong stocks and examine the relationship between these measures and the one-month ahead stock return over thirty-five years. First, we employ a stock's past three-year weekly return to compute idiosyncratic volatility. Second, we use a stock's past three-year maximum weekly return to create a MAX measure. We find that both IVOL and MAX are significant and negatively related to the one-month ahead stock return. Both effects co-exist in the Hong Kong stock markets and are robust after controlling for the financial crisis, January effect, and tiny stocks.

Keywords: Total volatility; Idiosyncratic volatility; Maximum weekly returns; Asset pricing; Weekly data; Hong Kong stock markets (search for similar items in EconPapers)
JEL-codes: G11 G12 (search for similar items in EconPapers)
Date: 2018
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