Retail investors pay over twice as much attention to local companies than non-local ones, based on Google searches. News volume and volatility amplify this attention gap. Attention appears causally related to perceived proximity: first, acquisition by a nonlocal company is associated with less...

Using the pandemic as a laboratory, we show that asset markets assign a time- varying price to firms' disaster risk exposure. In 2020 the cross-section of realized and expected stock returns reflected firms' different exposure to the pandemic, as measured by their vulnerability to social...

The purpose of this paper is to analyse the predictability of earnings information before the quarterly disclosure date. Two categories of firms are contrasted: the firms that announce better quarterly earnings than the prior period and the firms that do not. The paper uses a sample of 67...

The efficient market hypothesis describes an efficient market as one in which investors cannot consistently predict stock returns because prices instantly reflect all the information flowing into the market. However, return predictability has been documented in many markets. This study tests the...

Periods of economic turmoil distort the ability of stock prices to reflect the available information. In the last three decades, emerging markets experienced numerous crises. The major three of them are the Asian Financial Crisis (1997-1998), Global Financial Crisis (2007-2009) and Global...

Purpose: In this paper we try to explain US stock market variations and cash flow fundamentals by employing three different book-valued based ratios, First, we explore the explanatory capacity of the simple book-market ratio on time-varying expected returns, and procced on altering its...

In this paper, we establish a comparison between one of the most traded financial derivatives in the markets, the so-called catastrophe bonds (abbreviated as cat bonds) and the corporate bonds. In the first section, we start from a brief definition as well as some basic concepts. In section two,...

This paper evaluates the predictive performance of machine learning methods in forecasting European stock returns. Compared to a linear benchmark model, interactions and nonlinear effects help improve the predictive performance. But machine learning models must be adequately trained and tuned to...

In this study, we analyze illiquidity premia and their effect on the expected returns of German real estate securities. To this end, we use a unique data set that includes real estate stocks, real estate investment trusts (REITs), and open- and closed-end real estate funds for 2003–2017. We...

This paper shows that low-risk stocks significantly outperform high-risk stocks in the local China A-share market. The main driver of this low-risk anomaly is volatility, and not beta. A Fama–French style VOL factor is not explained by the Fama–French–Carhart factors, and has the strongest...