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This paper aims to investigate how different emotions affect the subsequent index futures returns. We test the forecasting regressions which predict the S&P 500 index futures returns with lagged text‐based emotion (anger, joy, fear, optimism, and gloom) indices and find asymmetric forecasting power exists between pessimism and optimism emotion indices. We show that only the text‐based anger index could reliably perform at predicting index futures return in‐sample and outperform the prevailing unconditional mean out‐of‐sample. Notably, the predictive power of the text‐based anger index persists after controlling for other emotion indices, investor sentiment indices, and fundamental variables known to predict the futures market. And the asset allocation conditioning on text‐based anger index can generate substantial economic benefits. Furthermore, the anger index influences the index futures return through both the discount rate and cash flow channels. [ABSTRACT FROM AUTHOR]

Analyst recommendations convey valuable market‐wide information which implies analyst rating should generate reliable predictability for future market returns. This paper examines the predictive regressions which forecast the S&P 500 index futures return and volatility with lagged text‐based analyst rating index (TAR index). Empirical evidence shows that the TAR index generates superior in‐sample predictability. This substantial predictability remains after controlling the business cycles, macroeconomic factors, and economic conditions. Also, the TAR index outperforms the prevailing mean out‐of‐sample and generates significant economic performance. Notably, the TAR index also delivers consistent predictive gains on the volatility of index futures returns. [ABSTRACT FROM AUTHOR]

In this paper, we show that the individual skewness, defined as the average of monthly skewness across firms, performs very well at predicting the return of S&P 500 index futures. This result holds after controlling for the liquidity risk or for the current business cycle conditions. We also find that individual skewness performs very well at predicting index futures returns out‐of‐sample. [ABSTRACT FROM AUTHOR]