Are extreme returns priced in the stock market? European evidence

Abstract

This paper revisits some recently found evidence in the literature on the cross-section of stock returns for a carefully constructed dataset of euro area stocks. First, we find evidence of a negative crosssectional relation between extreme positive returns and average returns after controlling for characteristics such as momentum, book-to-market, size, liquidity and return reversal. We argue that this is the case because these stocks have lottery-like characteristics. Second, when we control for this relation, the idiosyncratic volatility puzzle seems to disappear. When extreme positive returns are included in the regression, we find a weak but positive relation between idiosyncratic volatility and returns. Lastly, the maximum return effect holds when we control for skewness. Moreover, skewness is on its own negatively related to returns in our sample, as several asset pricing models predict.

Have capital market anomalies worldwide attenuated in the recent era of high liquidity and trading activity?

“…Besides a country extension, we contribute to the literature by methodological innovation, which not only ensures the robustness of our new international results but also sheds light on the stability of Chordia et al (2014)'s US results. First, because financial returns and especially anomaly returns exhibit quite large extremes (see Bali et al, 2011;Annaert et al, 2013;Daniel and Moskowitz, 2016), which can distort classic ordinary least squares (OLS) regressions (see Belsley et al, 1980), we supplement our simple regression analysis with several quantile regression (QR) settings. They are more robust to outliers, avoid assumptions about the parametric distribution of the error process and provide a richer characterisation of the data, allowing us to consider the impact of liquidity on the entire distribution of anomaly returns, not merely its conditional mean (see Koenker and Hallock, 2001).…”

Reversal and momentum patterns in weekly stock returns: European evidence

“…Our study gives an out‐of‐sample test to the existing literature and corroborates that the coexistence of reversal and momentum is not driven by a data snooping bias in the sense of Lo and MacKinlay (). We follow, among others, Rouwenhorst (), Annaert, De Ceuster, and Verstegen () and Walkshäusl (), who also use European stock markets as a new dataset to test the robustness of market anomalies like momentum and the MAX effect.…”

“…(1990b). We follow, among others, Rouwenhorst (1998), Annaert, De Ceuster, and Verstegen (2013) and Walkshäusl (2014), who also use European stock markets as a new dataset to test the robustness of market anomalies like momentum and the MAX effect.…”

Lottery preferences and the idiosyncratic volatility puzzle

“…Hou and Loh () evaluate the various alternative explanations for the IVOL puzzle and show that lottery preference‐based explanations capture a good portion of the puzzle. Using maximum daily returns over the past month (MAX) as a proxy for lottery‐like payoffs, Bali et al () and Annaert, De Ceuster, and Verstegen () show that controlling for MAX reverses the IVOL effect shown by Ang et al (, ). More recently, Cheon and Lee (forthcoming) find that the IVOL puzzle is stronger in the high‐MAX quintile for international data.…”