Munich Personal RePEc Archive

Search of Attention in Financial Market

Chong, Terence Tai Leung and Li, Chen (2020): Search of Attention in Financial Market.

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This study employs correlation coefficients and the factor-augmented vector autoregressive (FAVAR) model to investigate the relationship between the stock market and investors’ sentiment measured by big data. The investors’ sentiment index is constructed from a pool of relative keyword series provided by the Baidu Index. We target two composite stock indices, namely the Hang Seng Index and the Shanghai Composite Index. We first compute the Pearson product-moment correlation coefficient to find the degree of correlation between keywords and composite stock price indices. Then, we apply the FAVAR model to obtain the impulse response of stock price to the investors’ sentiment index. Finally, we examine the leading effects of keywords on stock prices using lagged correlation coefficients. We obtain two main findings. First, a strong correlation exists between investors’ sentiment and composite stock price: Second, before and after the launch of the Shanghai-Hong Kong Stock Connect, the keywords affecting the fluctuation of the Hang Seng Index are different.

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