CCER讨论稿:Does Measurement Error Matter in Volatility Forecasting? Empirical Evidence from the Chinese Stock Market

发布日期:2018-09-17 09:55:42    来源:北京大学国家发展研究院

E2018019                                                       2018-09-16

Yajing Wang,  Zhuo Huang, Fang Liang, Tianyi Wang*

Abstract: Based on methods from Bollerslev et al. (2016), we explicitly account for the heteroskedasticity in the measurement errors and high volatility in Chinese stock prices and propose a new realized volatility forecasting model, LogHARQ, to forecast the realized volatility of Chinese stock index futures and options. Out-of-sample findings suggest that the LogHARQ model performs better than existing logarithmic and linear forecast models, particularly when the realized quarticity is large. In an economic sense, using the LogHARQ model for volatility forecasting leads to significant utility gains for investors.

Keywords: Realized volatility, Measurement errors, Volatility forecasting, Chinese stock market

* Yajing Wang is at the School of Banking and Finance, University of International Business and Economics, Beijing, China. Zhuo Huang is at the National School of Development, Peking University, Beijing, China. Fang Liang is at the National School of Development, Peking University, Beijing, China. Tianyi Wang is at the School of Banking and Finance, University of International Business and Economics, Beijing, China. The authors claim financial support from the National Natural Science Foundation of China (71671004).

* Corresponding author: Tianyi Wang. School of Banking and Finance, University of International Business and Economics, Beijing 100029, P.R. China, Tel:86-10-64492513, Email: tianyiwang@uibe.edu.cn.

讨论稿下载 E20180019

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