A dynamic factor model applied to investor sentiment in the European context

  • Received February 18, 2021;
    Accepted March 19, 2021;
    Published March 23, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.18(1).2021.25
  • Article Info
    Volume 18 2021, Issue #1, pp. 299-314
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This work is licensed under a Creative Commons Attribution 4.0 International License

This paper proposes an Investor Sentiment Index for the European market and tests its predictability power over returns and volatility. The constructed Investor Sentiment Index for Europe draws upon three well-established and two recent individual sentiment proxies through a novel dynamic factor modeling addressed to behavioral finance. The index is obtained through an extended period of analysis and validated with other sentiment index measures. The work relies on individual sentiment proxies based on a dynamic factor model and tests it using a TGARCH model for volatility and returns. It carries out an in-sample and out-of-sample analysis to examine this sentiment index’s forecasting power over returns sustained on a recursive rolling window prediction against Fama and French’s three-factor model. The findings demonstrate that the proposed index closely predicts STOXX600 variance and returns and confirms a strong spillover effect between European and US stock markets. This study also concludes that the proposed European Sentiment Index is a valid alternative method for investors to monitor and predict market behaviors. The developed sentiment measure is a vital market prediction movement tool for financial information providers, investors, bankers, and financial analysts. The research combines the sentiment index with a TGARCH approach over the extended period of analysis and validates the method with other sentiment index measures. An in-sample and out-of-sample study confirms the predictive power of this work’s sentiment over returns compared to Fama and French’s three-factor model.

Acknowledgment
This work is funded by National Funds through the FCT – Foundation for Science and Technology, I.P., within the scope of the project Refª UIDB/05583/2020. Furthermore, we would like to thank the Research Centre in Digital Services (CISeD) and the Polytechnic of Viseu for their support.

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    • Figure 1. Comparison of standardized values of the proposed European sentiment index, standardized values of pc1 or EURsent index (Reis & Pinho, 2020b), and standardized values of US sentiment index (Baker & Wurgler (2006)
    • Figure 2. Standardized Stoxx600 returns variance obtained from the ARCH model and standardized sentiment index (stdf)
    • Figure 3. The adjusted R2 for a 50-month rolling window returns forecast from 1999–2018, for horizons 0 to 4 with Newest t statistics
    • Figure 4. The sentiment coefficient for a 50-month rolling window returns forecast from 1999–2018, for horizons 0 to 4 with Newest t statistics
    • Table 1. Descriptive statistics and definition of variables
    • Table 2. TGARCH model for log of Stoxx600 return and volatility
    • Table 3. Out-of-sample forecasting results
    • Conceptualization
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Data curation
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Formal Analysis
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Funding acquisition
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Investigation
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Methodology
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Project administration
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Resources
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Software
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Supervision
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Validation
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Visualization
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Writing – original draft
      Pedro Manuel Nogueira Reis, Carlos Pinho
    • Writing – review & editing
      Pedro Manuel Nogueira Reis, Carlos Pinho