Further empirical evidence on the forecasting of volatility with smooth transition exponential smoothing |
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Institution: | 1. Faculty of Economics and Management, Nanchang University, China;2. Saïd Business School, University of Oxford, United Kingdom;3. Department of Management and Marketing, Universiti Putra Malaysia, Malaysia;1. Narodowy Bank Polski, Poland;2. University of Lodz, Poland;1. Aletheia University, Taiwan;2. National Taichung University of Science and Technology, Taiwan;1. China Economics and Management Academy, Central University of Finance and Economics, No. 39 South College Road, Haidian District, 100081 Beijing, China;2. School of Finance, Jiangxi University of Finance and Economics, Nanchang, China;3. School of Economics, Jiangxi University of Finance and Economics, Nanchang, 330013, China |
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Abstract: | Smooth transition exponential smoothing (STES) uses a logistic function of a user-specified transition variable as adaptive time varying smoothing parameter. This paper empirically addresses three aspects of the use of STES for volatility forecasting. Previous empirical results showed the method performing well in comparison with fixed parameter exponential smoothing and a variety of GARCH models. However, those results related only to forecasting weekly volatility. In this paper, we address the use of STES for forecasting daily volatility. A second issue that we evaluate is the robustness of STES in the presence of extreme outlying observations. The third aspect that we consider is the use of trading volume within a transition variable in the STES method. Our simulation results suggest that STES performs well in terms of robustness, when compared with standard methods and several alternative robust methods. Analysis using stock return data shows that STES has the potential to outperform standard and robust forms of fixed parameter exponential smoothing and GARCH models. The results suggest the use of the sign and size of past shocks as STES transition variables, and provide no clear support for the incorporation of trading volume in a transition variable. |
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Keywords: | Smooth transition exponential smoothing Daily volatility forecasting Robustness Trading volume |
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