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The colour of finance words in Chinese

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  • Yao, Kai
  • Zheng, Zexu
  • Liu, Cai

Abstract

This study extends the research of García et al. (2023) by leveraging their robust-MNIR algorithm to construct a sentiment lexicon for the Chinese stock market. We investigate whether this data-driven approach effectively captures the sentiment expressed in financial text within this unique market context. The Chinese lexicon demonstrates superior performance relative to existing dictionaries in market segments with high institutional ownership, particularly when capturing machine-learned negative sentiment. These results not only validate the cross-lingual applicability of the robust-MNIR algorithm but also provide empirical evidence for the heterogeneity of investor sentiment interpretation, highlighting the importance of market-specific characteristics in sentiment analysis.

Suggested Citation

  • Yao, Kai & Zheng, Zexu & Liu, Cai, 2025. "The colour of finance words in Chinese," Pacific-Basin Finance Journal, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:pacfin:v:94:y:2025:i:c:s0927538x2500191x
    DOI: 10.1016/j.pacfin.2025.102854
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    References listed on IDEAS

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