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Search of Attention in Financial Market

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  • Chong, Terence Tai Leung
  • Li, Chen

Abstract

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.

Suggested Citation

  • Chong, Terence Tai Leung & Li, Chen, 2020. "Search of Attention in Financial Market," MPRA Paper 99003, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:99003
    as

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    References listed on IDEAS

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    More about this item

    Keywords

    Baidu Index; Stock Connect;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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