We introduce a real-time dispersion measure based on cross-sectional stock returns explicitly designed to capture retail-driven speculative episodes. Elevated return dispersion effectively identifies periods characterized by intensified retail investor trading behaviors, driven by salience, diagnostic expectations, and extrapolative beliefs. During these high-dispersion states, momentum strategies collapse, and short-term reversals become dominant. Conditioning momentum strategies on our dispersion measure resolves the longstanding puzzle of missing momentum in retail-intensive markets such as China, substantially enhancing profitability. A dynamic rotation strategy between momentum and short-term reversal portfolios guided by dispersion states achieves annualized Sharpe ratios nearly double those of static approaches. Extending our analysis internationally, we employ Google search trends as proxies for retail investor attention, confirming that dispersion robustly predicts momentum and reversal returns globally. Our findings underscore the behavioral channel through which retail-driven speculation conditions momentum dynamics, providing clear implications for dynamic portfolio management strategies.

This study investigates the relationship between investors’ prior gains or losses and their adoption of extrapolative beliefs. Our findings indicate that investors facing prior losses tend to rely on optimistic extrapolative beliefs, whereas those experiencing prior gains adopt pessimistic extrapolative beliefs. These results support the theory of motivated beliefs. The interaction between the capital gain overhang and extrapolative beliefs results in noteworthy mispricing, yielding monthly returns of approximately 1%. Motivated extrapolative beliefs comove with investors’ survey expectations and trading behavior, and help explain momentum anomalies. Additionally, households are susceptible to this belief distortion. Institutional investors can avoid overpriced stocks associated with motivated (over-)optimistic extrapolative beliefs.

This study investigates the relationship between investors’ prior gains or losses and their adoption of extrapolative beliefs. Our findings indicate that investors facing prior losses tend to rely on optimistic extrapolative beliefs, whereas those experiencing prior gains adopt pessimistic extrapolative beliefs. These results support the theory of motivated beliefs. The interaction between the capital gain overhang and extrapolative beliefs results in noteworthy mispricing, yielding monthly returns of approximately 1%. Motivated extrapolative beliefs comove with investors’ survey expectations and trading behavior, and help explain momentum anomalies. Additionally, households are susceptible to this belief distortion. Institutional investors can avoid overpriced stocks associated with motivated (over-)optimistic extrapolative beliefs.

How do expectation biases causally affect households’ financial decisions? We exploit a unique setting and study the repayment decision in solar loans, in which households borrow to purchase and install solar photovoltaic (PV) systems. Electricity production – the benefit that solar panels generate – primarily depends on sunshine duration. This creates exogenous within-person across-period variation in recent signals that borrowers observe and thereby expectations of future electricity production. We find that a one-standard-deviation decrease in sunshine duration in the week right before the repayment date leads to a 20.8% increase of delinquency, even though deviated past sunshine duration does not predict that in the future. Survey evidence shows that agents make more positive forecasts of future electricity production after experiencing longer sunshine duration in the past week. We examine a battery of alternative explanations and rule out mechanisms based on liquidity constraints and wealth effects.