We use firm characteristics to estimate the enduring momentum probabilities for past winners (losers) to continue to be future winners (losers). The enduring momentum probability is significantly related to stock return persistence and explains cross-sectional expected returns. In addition, it...

Time-series momentum (TSMOM) and moving average (MA) trading rules are closely related; however there are important differences. TSMOM signals occur at points that coincide with a MA direction change, whereas MA buy (sell) signals only require price to move above (below) a MA. Our empirical...

Active ETFs are less liquid than their underlying portfolios. This finding, which contrasts with that for passive ETFs, is attributed to uncertainty of future holdings of active ETFs. In addition, while diversification generally reduces firm-specific information asymmetry and improves portfolio...

We consider the frequency and correlation of extreme return observations or “jumps” across equities, Treasury bonds, corporate bonds, currencies, commodities, and real estate. Understanding more about jumps is important to investors as diversification across asset classes is diminished if...

Brokers have access to order-flow data, which they can use to enhance the returns they earn from short selling. However, brokers also have a fiduciary duty to place their clients’ interests before their own. We test whether brokers exploit their informational advantage and earn larger returns...