Existing research indicates that it is possible to forecast potential long-term returns in the S&P 500 for periods of more than 10 years using the cyclically adjusted price-to-earnings ratio (CAPE). This paper concludes that this relationship has also existed internationally in 17 MSCI Country...

This paper studies whether investor sentiment can predict future Mexican stock market returns. Furthermore, we examine the dynamic correlation between sentiment and returns. Lastly, we examine whether sentiment innovations influence unexpected returns. We find that sentiment has significant...

The predictability of stock market is of great interest to both reseachers and investors. Despite voluminous evidence of in-sample predictability, the out-of-sample predictability of stock returns remains an ongoing debate. In this paper, motivated by both the financial theories and the well...

This paper uses the tools of computational linguistics to analyze the qualitative part of annual reports of UK listed companies. More specifically, the frequency of words associated with different language indicators is measured and used to forecast future stock returns. We find that two of...

In this paper, we extend the literature on crash prediction models in three main ways. First, we explicitly relate crash prediction measures and asset pricing models. Second, we present a simple, effective statistical significance test for crash prediction models. Finally, we propose a...

Empirical financial literature documents the evidence of mean reversion in stock prices and the absence of out-of-sample return predictability over periods shorter than 10 years. The goal of this paper is to test the random walk hypothesis in stock prices and return predictability over periods...

The paper re-examines whether investors can predict oil and gas stock prices for abnormal returns using autocorrelation-based trading and filter rules and moving average based strategies. Short and long lengths moving averages were employed and their performances measured against the returns...

Predicting stock market crashes and corrections is a focus of interest for both researchers and practitioners. Several prediction models have been developed, mostly on mature financial markets. In this paper, we investigate whether fundamental crash predictors, the price-to-earnings ratio, the...

Movements in the stock market should reflect expectations regarding future economic conditions and lead the macroeconomy. However, evidence for stock returns providing such predictive power is mixed. We argue this arises as stock returns are noisy and consider the predictive ability of derived...

This paper proposes a novel approach to extracting option-implied equity premia, and empirically examines the information content of these risk premia for forecasting the stock market return. Our approach does not require specifying the functional form of the pricing kernel, and does not impose...