The extant research indicates that analysts' long-term earnings growth forecasts are especially optimistic for past winners, and have little predictive power to distinguish between high-growth and low-growth firms. In explaining the poor informational value of analysts' long-term earnings growth...

We present a simple dynamical model of stock index returns which is grounded on the ability of the Cyclically Adjusted Price Earning (CAPE) valuation ratio devised by Robert Shiller to predict long-horizon performances of the market. More precisely, we discuss a discrete time dynamics in which...

Firms whose quarterly earning announcements closely meet the most recent analyst consensus forecast enjoy higher long-lasting future returns. These firms tend to be larger and are followed by more analysts, whose forecasts have a smaller dispersion. While the proportion of past quarters when...

This paper introduces a novel, option-free methodology to calculate the tail risk premium for individual stocks, and examines the characteristics of this premium in the cross section of stock returns. The existence of a premium for bearing negative tail risk is significantly associated with...

We examine the predictive ability of the aggregate earnings yield for market returns and earnings growth by estimating variance decompositions at multiple horizons. Based on weighted long-horizon regressions, we find that most of the variation in the earnings yield is due to return...

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands/U.K. (1629-1812), U.K. (1813-1870) and U.S. (1871-2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for...

Forecasting the future prices of stock by analyzing the past and current price movements in determining the trend are always areas of interest of Chartists who believe in studying the action of the market itself rather than the past and current performances of the company. Stock price prediction...

This paper examines whether security analyst earnings forecasts for firms primarily operating in the gold market can be utilised to predict returns on the price of gold.We first demonstrate that analysts are at least in part basing their earnings forecasts for gold firms on the return...

This paper examines to what extent the momentum spread ratio (MSR) can predict momentum profits. The momentum spread ratio as a potential proxy of investor underreaction can significantly predict the momentum, industry momentum, and residual momentum, especially after 1994, suggesting that...

We examine the potential of ChatGPT, and other large language models, in predicting stock market returns using sentiment analysis of news headlines. We use ChatGPT to indicate whether a given headline is good, bad, or irrelevant news for firms' stock prices. We then compute a numerical score and...