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Empirical Research on the Fama-French Three-Factor Model and a Sentiment-Related Four-Factor Model in the Chinese Blockchain Industry

Author

Listed:
  • Ziyang Ji

    (International Business School Suzhou, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China)

  • Victor Chang

    (School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough TS1 3BX, UK)

  • Hao Lan

    (International Business School Suzhou, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China)

  • Ching-Hsien Robert Hsu

    (Department of Computer Science and Information Engineering, Asia University, Taichung 400-439, Taiwan
    Department of Medical Research, China Medical University, Taichung 400-439, Taiwan
    School of Mathematics and Big Data, Foshan University, Foshana 528000, China)

  • Raul Valverde

    (John Molson School of Business, Concordia University, Montreal, QC G1X 3X4, Canada)

Abstract

As one of the most significant components of financial technology (FinTech), blockchain technology arouses the interests of numerous investors in China, and the number of companies engaged in this field rises rapidly. The emotion of investors has an effect on stock returns, which is a hot topic in behavioral finance. Blockchain is an essential part of FinTech, and with the fast development of this technology, investors’ sentiment varies as well. The online information that directly reflects investors’ mood could be utilized for mining and quantifying to construct a sentiment index. For a better understanding of how well some factors adequately explain the return of stocks related to blockchain companies in the Chinese stock market, the Fama-French three-factor model (FFTFM) will be introduced in this paper. Furthermore, sentiment could be a new independent variable to enhance the explanatory power of the FFTFM. A comparison between those two models reveals that the sentiment factor could raise the explanatory power. The results also indicate that the Chinses blockchain industry does not own the size effect and book-to-market effect.

Suggested Citation

  • Ziyang Ji & Victor Chang & Hao Lan & Ching-Hsien Robert Hsu & Raul Valverde, 2020. "Empirical Research on the Fama-French Three-Factor Model and a Sentiment-Related Four-Factor Model in the Chinese Blockchain Industry," Sustainability, MDPI, vol. 12(12), pages 1-22, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:12:p:5170-:d:375874
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    References listed on IDEAS

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    Cited by:

    1. Ali, Mohd Helmi & Chung, Leanne & Kumar, Ajay & Zailani, Suhaiza & Tan, Kim Hua, 2021. "A sustainable Blockchain framework for the halal food supply chain: Lessons from Malaysia," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    2. Garg, Poonam & Gupta, Bhumika & Chauhan, Ajay Kumar & Sivarajah, Uthayasankar & Gupta, Shivam & Modgil, Sachin, 2021. "Measuring the perceived benefits of implementing blockchain technology in the banking sector," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    3. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "How well do investor sentiment and ensemble learning predict Bitcoin prices?," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean Michel & Guesmi, Khaled, 2021. "Is Bitcoin rooted in confidence? – Unraveling the determinants of globalized digital currencies," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    5. Ante, Lennart & Fiedler, Ingo & Strehle, Elias, 2021. "The impact of transparent money flows: Effects of stablecoin transfers on the returns and trading volume of Bitcoin," Technological Forecasting and Social Change, Elsevier, vol. 170(C).

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