A multidimensional Bayesian model to test the impact of investor sentiment on equity premium

Mehdi Mili, Jean‐Michel Sahut (), Frédéric Teulon and Lubica Hikkerova
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Mehdi Mili: University of Bahrain
Jean‐Michel Sahut: IDRAC Business School
Lubica Hikkerova: IPAG Business School

Annals of Operations Research, 2024, vol. 334, issue 1, No 33, 919-939

Abstract: Abstract Prior research hasn't provided convincing empirical support for two crucial issues: how investor sentiment can be measured, and can it be used to forecast stock market performance? To bridge this divide, we present a novel empirical technique based on investor sentiment and Bayesian vector autoregressive (BVAR) models to estimate stock returns. Sentiment has always had a substantial impact on the determination of stock prices in US financial markets, even during the subprime crisis. Impulse responses show that a positive shock to investor sentiment pushes equity returns above their equilibrium positions, with the maximum deviation being achieved around two months after the trigger event followed by a return to equilibrium after 6 months. Compared to BVAR models with priors commonly used in the literature, our model enables a very efficient restriction of the coefficients to be estimated without reducing the explanatory power of the model. Moreover, it provides better forecasting of stock returns than other BVAR models beyond 3 months.

Keywords: Bayesian approach; Equity premium; Sentiment; Forecasting; Stochastic priors (search for similar items in EconPapers)
JEL-codes: C11 C52 C53 E37 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-023-05165-0

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