There is evidence that volatility forecasting models that use intraday data produce superior forecast accuracy as compared with that delivered by the models that use daily data.Stock Market Forecast: Potential Volatility - October 29th, 2012
However, this evidence is still sparse and incomplete in the stock markets. This paper extends previous studies on forecasting stock market volatility in several important directions and comprehensively assesses the gains in forecast accuracy provided by intraday data.
First, we use an extensive set of intraday data on 28 single stocks and 23 stock market indices. Second, in our study we use forecast horizons ranging from 1 day to 6 months.
Third, we compare forecasting abilities of several competing models.
We find that the amount of gains depends on the length of the forecast horizon, on the forecasting model, and on whether the volatility is forecasted for a single stock or a stock market index.
Thus, the gains from using intraday data are rather significant. Surprisingly, we find that the gains in predictive accuracy from intraday data persist over longer forecast horizons and are greater for stock market indices than los 7 pasos forex single stocks.
Forecasting Volatility in the New Zealand Stock Market
Li, Xingyi and Zakamulin, Valeriy, Forecasting Stock Market Volatility: The Gains from Using Intraday Data Forecasting volatility in stock market 3, Serviceboks N Kristiansand, VEST AGDER Norway Phone.
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Xingyi Li School of Business and Law, University of Agder Valeriy Zakamulin University of Agder - School of Business and Law. Abstract There is evidence that volatility forecasting models that use intraday data produce superior forecast accuracy as compared with that delivered by the models that use daily data.
Forecasting Stock Market Volatility: Evidence From Fourteen Countries by Ercan Balaban, Asli Bayar, Robert W. Faff :: SSRN
Xingyi Li Contact Author School of Business and Law, University of Agder email Serviceboks N Kristiansand, VEST AGDER Norway Phone.
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