The impact of Baidu Index sentiment on the volatility of China’s stock markets

Jianchun  Fang; Giray Gozgor; Chi Keung Lau; Zhou Lu

doi:10.1016/j.frl.2019.01.011

The impact of Baidu Index sentiment on the volatility of China’s stock markets

Jianchun Fang, Giray Gozgor, Chi Keung Lau, Zhou Lu

Research output: Contribution to journal › Article › peer-review

88 Citations (Scopus)

Abstract

This paper examines the relationship between investor sentiment and the volatility of China's stock markets. We use the data from Baidu, China's leading search engine, for information on investor sentiment. In two different Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, the baseline model and the Baidu-Index extended model, we forecast the return volatility of China's stock markets. We find that the Baidu-Index extended model performs better than the baseline model. This paper shows that the search volume of relevant key words from Baidu Index improves volatility forecasting of China's stock markets.

Original language	English
Article number	101099
Number of pages	8
Journal	Finance Research Letters
Volume	32
Early online date	29 Jan 2019
DOIs	https://doi.org/10.1016/j.frl.2019.01.011
Publication status	Published - 1 Jan 2020

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BaiduIndexSentiment-FRL-V2.0Accepted author manuscript, 405 KBLicence: CC BY-NC-ND

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title = "The impact of Baidu Index sentiment on the volatility of China{\textquoteright}s stock markets",

abstract = "This paper examines the relationship between investor sentiment and the volatility of China's stock markets. We use the data from Baidu, China's leading search engine, for information on investor sentiment. In two different Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, the baseline model and the Baidu-Index extended model, we forecast the return volatility of China's stock markets. We find that the Baidu-Index extended model performs better than the baseline model. This paper shows that the search volume of relevant key words from Baidu Index improves volatility forecasting of China's stock markets.",

keywords = "Investor sentiment, Stock market volatility, Baidu-Index, GARCH models, Search engine, China",

author = "Jianchun Fang and Giray Gozgor and Lau, {Chi Keung} and Zhou Lu",

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N2 - This paper examines the relationship between investor sentiment and the volatility of China's stock markets. We use the data from Baidu, China's leading search engine, for information on investor sentiment. In two different Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, the baseline model and the Baidu-Index extended model, we forecast the return volatility of China's stock markets. We find that the Baidu-Index extended model performs better than the baseline model. This paper shows that the search volume of relevant key words from Baidu Index improves volatility forecasting of China's stock markets.

AB - This paper examines the relationship between investor sentiment and the volatility of China's stock markets. We use the data from Baidu, China's leading search engine, for information on investor sentiment. In two different Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, the baseline model and the Baidu-Index extended model, we forecast the return volatility of China's stock markets. We find that the Baidu-Index extended model performs better than the baseline model. This paper shows that the search volume of relevant key words from Baidu Index improves volatility forecasting of China's stock markets.

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KW - Stock market volatility

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KW - GARCH models

KW - Search engine

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JF - Finance Research Letters

SN - 1544-6123

M1 - 101099

ER -

The impact of Baidu Index sentiment on the volatility of China’s stock markets

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