Reassessing the Predictability of the Investor Sentiments on US Stocks: The Role of Uncertainty and Risks

Abstract

Abstract We examine the predictive power of US investor sentiments on US sectoral returns and aggregated S&P 500 index in the presence of different risk and uncertainty indices. Investor sentiments are measured using the sentiment index proposed by Baker and Wurgler (2006). We also use bearish and bullish investor sentiment indices i.e., AAII sentiment indices, published by the American association of individual investors. We also use different risk and uncertainty indices i.e., economic policy uncertainty, financial uncertainty, geopolitical risk, and US equity market volatility. Results of the baseline model (i.e., the single model where the only predictor is sentiment index) show that the forecasting power of the predictor is weak. Augmenting the baseline model to account for uncertainty measures shows that the uncertainty's transmission impact is more accurate for out-of-sample forecasts than the single-factor model. We also highlight that the performance of the multi-factor predictive model incorporating USS B&W is superior to the benchmark model. Policy implications of the results are also discussed.