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Forecasting stock market volatility: The role of technical variables

Li Liu and Zhiyuan Pan

Economic Modelling, 2020, vol. 84, issue C, 55-65

Abstract: Accurate volatility forecasts are required by both market participants and policy makers. In this paper, we forecast stock return volatility by using a wide range of technical indicators constructed based on the past behavior of stock price, volatility and trading volume. Our out-of-sample results indicate that the incorporation of technical variables in the autoregression benchmark can produce significantly more accurate volatility forecasts. The forecasting performance of the combination of technical indicators is further compared with that of the popular economic indicators. Technical variables perform better than economic variables when the economy is an expansion, while the economic variables generate more accurate forecasts when the economy belongs a recession. These two types of variables provide complementary information over the business cycle. We obtain more reliable forecasts by combining all economic and technical information together than by combining either type of information alone.

Keywords: Predictive regressions; Technical indicators; Macroeconomic variables; Forecast combinations; Business cycle (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.econmod.2019.03.007

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