We propose a new predictor - the innovation in the daily return minimum in the U.S. stock market () - for predicting … international stock market returns. Using monthly data for a wide range of 17 MSCI international stock markets during the period … international stock markets: negatively predicts the next-month stock market returns. The results remain robust after controlling …

We utilize Bayesian model averaging to estimate a stochastic discount factor (SDF) for single-stock options. A Bayesian …

China's stock market greatly outperformed other national markets during the first several months of the COVID-19 … of 2020. Our analysis finds clear evidence that these interventions raised implied stock market volatility but little … evidence that they influenced stock price levels. We also consider policy actions that restricted short selling, limited stock …

Accurately predicting stock market movements remains a critical challenge in finance, driven by the increasing role of …

This study examines stock borrowing costs in Japan's centralized lendable stock market, focusing on differences between …, and new stock borrowing patterns. Regression models are utilized to explore the relationships between these factors and … highlight the role of centralized lendable stock markets in enhancing pricing efficiency without hindering trading activities. …

thresholds is carried out for each of the main stock market indices to estimate the changes in these borders that affect and …