This paper provides a model to interpret the relative behavior of expected returns of high- and low-resilience assets from the time of the COVID-19 pandemic, including a novel definition of disaster based on COVID-19 intensity. The setup allows us to disentangle the probability of disaster and...

This study examines the out-of-sample predictability of expected skewness of oil price returns, which serves as a metric for global future risks, as we show statistically through the association with crises of different nature, for stock returns of 10 (8 advanced plus two emerging) countries...

This study examines the impact of China's "Zero-COVID" policies on stock returns in the healthcare sector from January 2020 to December 2022. Using panel regression analysis, we find that increases in the Stringency Index increased healthcare stock returns. In contrast, vaccination rates are...

Are carbon emissions priced in equity markets? The literature is split with different approaches yielding conflicting results. We develop a stylized model showing that, if emissions are priced, stock returns depend on expected emissions and the product of the innovation in emissions and the...

Purpose - Contrary to the developed markets, where ESG (environmental, social and governance) investing has received considerable attention, the extant literature in the context of emerging markets remains fragmented and scarce. To fill this gap, the study examines the financial performance of...

We studied decades-long (1980 to 2024) historic distributions of accumulated S&P500 returns, from daily returns to those over several weeks. The time series of the returns emphasize major upheavals in the markets - Black Monday, Tech Bubble, Financial Crisis, and the COVID pandemic - which are...

This study employs asymmetric quantile regression to investigate the asymmetric impact of WTI crude oil prices and economic policy uncertainty (EPU) on stock market returns from May 2014 to December 2024 in oil-importing (China, India, Germany, Italy, Japan, USA, and South Korea) and...

We employ a cross-quantilogram approach to assess relationships between quantiles of stock returns and sovereign yields, in the U.S. and Germany, in the period 1990-2024. Specifically, we focus on the lowest 5% quantile of stock returns and the highest 5% quantile of bond returns, providing...

Over the past decade, multifactor models have shown enhanced capability compared to single-factor models in explaining asset return variability. Given the common assertion that higher risk tends to yield higher returns, this study empirically examines the augmented human capital six-factor...

Purpose - This study examines the impact of firm-level climate risk exposure (FCRE) on firm stock liquidity by using a sample of Indian-listed firms from the financial years 2003-2004 to 2022-2023. Further, it endeavors to investigate the moderating role of environmental, social and governance...

We study a direct, firm-level measure of investor sentiment derived from social media (BTSS sentiment). While related to firm fundamentals, BTSS sentiment contains a substantial non-fundamental component. We decompose sentiment into fundamental and pure sentiment and show that return...

Recent studies highlight the superior performance of non-linear machine learning models, such as neural networks, over traditional linear models in predicting cross-sectional stock returns. These models are capable of capturing complex non-linear interactions between predictive signals and...