**4. Conclusions**

This paper applies the sentiment index in regression models to predict US and European stock market returns. Many measurements are experimented, from direct sentiment indices, like surveys, to indirect measures of investor sentiment, such as the ones calculated by (Huang et al. 2014; Baker and Wurgler 2006, 2007). Differently than the previous literature, we control for a set of variables often used in return predictability and apply Bayesian inference to reduce parameter uncertainty due to the short sample, in particular for the European example.

As regards the American example, the results showed that globally sentiment has a negative impact on the stock market returns and BW resulted to have the highest predictive power. With respect to the European market, evidence shows weak findings and no relationship is found. Finally, the results show the presence of spillover effect between the two markets. Therefore, it can be concluded that U.S. and EU are two interdependent markets. In the end, this idea can justify the weak outputs on the European markets. From an economic standpoint, affected from globalisation and quick communication, Europe could be more prone to follow the influence of the American sentiment, because of the stronger economy.

Unfortunately, due to unavailability of data, the analysis is conducted on a limited range. The short period is a limitation on estimating the best model, since there could be omitted factors influencing the estimation. The use of Bayesian priors limits somewhat such effects. However, in future works it could be interesting to explore the difference between the rational and irrational factors of the sentiment, deepening the irrational analysis (i.e., the residual part).

**Author Contributions:** The work was equally divided between the two coauthors. The origin and development of the paper was a joint initiative. C.L.C. focused on collection of data and econometric analysis; F.R. worked on writing results and the working paper.

**Funding:** This work was supported by the Open Access Publishing Fund of the Free University of Bozen-Bolzano.

**Acknowledgments:** We thank the editor, two anonymous referees and Stefano Grassi for helpful comments and suggestions to improve this work. Chiara Limongi Concetto thanks the Italian Banking, Insurance, and Finance Federation to award the RIFET (Rome Investment Forum Empowers Talents) 2017 award.

**Conflicts of Interest:** The authors declare no conflict of interest.
