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Is Baidu index really powerful to predict the Chinese stock market volatility? New evidence from the internet information

Qiaoqi Lang, Jiqian Wang, Feng Ma, Dengshi Huang and Mohamed Wahab Mohamed Ismail

China Finance Review International, 2021, vol. 13, issue 2, 263-284

Abstract: Purpose - This paper verifies whether popular Internet information from Internet forum and search engine exhibit useful content for forecasting the volatility in Chinese stock market. Design/methodology/approach - First, the authors’ study commences with several HAR-RV-type models, then the study amplifies them respectively with the posting volume and search frequency to construct HAR-IF-type and HAR-BD-type models. Second, from in-sample and out-of-sample analysis, the authors empirically investigate the interpretive ability, forecasting performance (statistic and economic). Third, various robustness checks are utilized to reconfirm the authors’ findings, including alternative forecast window, alternative evaluation method and alternative stock market. Finally, the authors further discuss the forecasting performance in different forecast horizons (h = 5, 10 and 20) and asymmetric effect of information from Internet forum. Findings - From in-sample perspective, the authors discover that posting volume exhibits better analytical ability for Chinese stock volatility than search frequency. Out-of-sample results indicate that forecasting models with posting volume could achieve a superior forecasting performance and increased economic value than competing models. Practical implications - These findings can help investors and decision-makers obtain higher forecasting accuracy and economic gains. Originality/value - This study enriches the existing research findings about the volatility forecasting of stock market from two dimensions. First, the authors thoroughly investigate whether the Internet information could enhance the efficiency and accuracy of the volatility forecasting concerning with the Chinese stock market. Second, the authors find a novel evidence that the information from Internet forum is more superior to search frequency in volatility forecasting of stock market. Third, they find that this study not only compares the predictability of the posting volume and search frequency simply, but it also divides the posting volume into “good” and “bad” segments to clarify its asymmetric effect respectively. Highlights -

Keywords: Realized volatility forecasting; Internet information; High-frequency data; Baidu index; Internet forum (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eme:cfripp:cfri-03-2021-0047

DOI: 10.1108/CFRI-03-2021-0047

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China Finance Review International is currently edited by Professor Chongfeng Wu and Professor Haitao Li

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