Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach

2021 ◽  
Author(s):  
Danyan Wen ◽  
Mengxi He ◽  
Yaojie Zhang ◽  
Yudong Wang
Keyword(s):  
Stock Market ◽  
Realized Volatility ◽  
Chinese Stock Market

Political uncertainty, realized volatility, and jumps in the Chinese stock market

2020 ◽  
pp. 1-5
Author(s):  
Yanhui Jiang ◽  
Liang Liu ◽  
Yun Hong
Keyword(s):  
Stock Market ◽  
Realized Volatility ◽  
Chinese Stock Market ◽  
Political Uncertainty

scholarly journals Measuring and Forecasting Volatility in Chinese Stock Market Using HAR-CJ-M Model

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Chuangxia Huang ◽  
Xu Gong ◽  
Xiaohong Chen ◽  
Fenghua Wen
Keyword(s):  
Stock Market ◽  
Sample Path ◽  
Realized Volatility ◽  
The Other ◽  
Chinese Stock Market ◽  
Momentum Effect ◽  
Forecasting Performance ◽  
The Future ◽  
Forecasting Volatility ◽  
Continuous Volatility

Basing on the Heterogeneous Autoregressive with Continuous volatility and Jumps model (HAR-CJ), converting the realized Volatility (RV) into the adjusted realized volatility (ARV), and making use of the influence of momentum effect on the volatility, a new model called HAR-CJ-M is developed in this paper. At the same time, we also address, in great detail, another two models (HAR-ARV, HAR-CJ). The applications of these models to Chinese stock market show that each of the continuous sample path variation, momentum effect, and ARV has a good forecasting performance on the future ARV, while the discontinuous jump variation has a poor forecasting performance. Moreover, the HAR-CJ-M model shows obviously better forecasting performance than the other two models in forecasting the future volatility in Chinese stock market.

scholarly journals Can the Baidu Index predict realized volatility in the Chinese stock market?

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Wei Zhang ◽  
Kai Yan ◽  
Dehua Shen
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Predictive Power ◽  
Realized Volatility ◽  
Trading Strategies ◽  
Time Series Models ◽  
Chinese Stock Market ◽  
Continuous Components ◽  
Long Term Impact

AbstractThis paper incorporates the Baidu Index into various heterogeneous autoregressive type time series models and shows that the Baidu Index is a superior predictor of realized volatility in the SSE 50 Index. Furthermore, the predictability of the Baidu Index is found to rise as the forecasting horizon increases. We also find that continuous components enhance predictive power across all horizons, but that increases are only sustained in the short and medium terms, as the long-term impact on volatility is less persistent. Our findings should be expected to influence investors interested in constructing trading strategies based on realized volatility.

Forecasting the realized volatility of the Chinese stock market: Do the G7 stock markets help?

2018 ◽  
Vol 501 ◽  
pp. 78-85 ◽  
Author(s):  
Huan Peng ◽  
Ruoxun Chen ◽  
Dexiang Mei ◽  
Xiaohua Diao
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Realized Volatility ◽  
Chinese Stock Market

scholarly journals An Exploration of Realized Volatility and Returns in the Chinese Stock Market

2021 ◽  
Vol 14 ◽  
pp. 304-314
Author(s):  
Kuaile Shi
Keyword(s):  
Stock Market ◽  
Turnover Rate ◽  
Predictive Power ◽  
Realized Volatility ◽  
Excess Return ◽  
Chinese Stock Market ◽  
Realized Variance ◽  
Market Returns ◽  
Stock Market Returns ◽  
Out Of Sample

This paper uses high-frequency stock index data to construct realized volatilities for the Chinese stock market and applies in-sample and out-of-sample  to test the predictive power of realized volatility on Chinese stock market returns. The empirical results show that realized volatility can significantly predict the excess return of the Chinese stock market in the next month, and the in-sample and out-of-sample regression models  are positive, and the out-of-sample  The p-value of the regression model is significant. And after controlling for a range of other stock predictor variables, we find that the regression coefficient of realized volatility is still significant, and we find that after adding realized volatility, the in-sample adj-  increases with the inclusion of realized volatility, suggesting that realized volatility does have components that are not explained by other economic variables. Also based on a different construction method, the realized variance still has significant predictive power after averaging the realized variance. After combining two different realized variance indicators, the predictive power is still better. In terms of economic interpretation, this paper finds that the predictive power of realized variance on stock returns is through influencing the turnover rate (market trading activity), which in turn influences stock market returns. We find that realized volatility has a significant effect on the turnover rate, and when we use realized volatility to predict the turnover rate, which in turn predicts the excess return, we find that the coefficient is highly significant, indicating that realized volatility can indeed cause changes in excess return by affecting the turnover rate.

Forecasting the realized volatility in the Chinese stock market: further evidence

2016 ◽  
Vol 48 (33) ◽  
pp. 3116-3130 ◽  
Author(s):  
Wang Pu ◽  
Yixiang Chen ◽  
Feng Ma
Keyword(s):  
Stock Market ◽  
Realized Volatility ◽  
Chinese Stock Market

Online collective emotion and Chinese stock market

2013 ◽  
Author(s):  
Hao Chen ◽  
Kai Sheng Lai
Keyword(s):  
Stock Market ◽  
Chinese Stock Market ◽  
Collective Emotion
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