Journal
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume 481, Issue -, Pages 153-159Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.physa.2017.04.020
Keywords
Volatility forecasts; Realized skewness and kurtosis; Realized volatility; HAR-RV; MF-DFA
Categories
Funding
- National Natural Science Foundation of China [71371157, 71401077, 71671145]
- fundamental research funds for the central universities [26816WBR01, 2682017WCX01]
- humanities and social science fund of the ministry of education [14YJC790073]
- Scientific and Technological Research Program of Chongqing Municipal Education Commission [KJ1601206]
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In this study, we investigate the predictability of the realized skewness (RSK) and realized kurtosis (RKU) to stock market volatility, that has not been addressed in the existing studies. Out-of-sample results show that RSK, which can significantly improve forecast accuracy in mid- and long-term, is more powerful than RKU in forecasting volatility. Whereas these variables are useless in short-term forecasting. Furthermore, we employ the realized kernel (RK) for the robustness analysis and the conclusions are consistent with the RV measures. Our results are of great importance for portfolio allocation and financial risk management. (C) 2017 Elsevier B.V. All rights reserved.
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