A Behavioral Analysis of Investor Sentiment During Systemic Crisis

Abstract This study examines how investor sentiment, shaped by behavioral biases, influenced decision-making during the 2007–2009 financial crisis. Focusing on two key biases—herding behavior and loss aversion - we analyze daily return data for 30 large-cap U.S. companies. To detect herding, we apply the Cross-Sectional Absolute Deviation (CSAD) methodology, which measures how closely individual returns track the market return. Regression results confirm non-linear dispersion patterns indicative of herding, particularly during periods of extreme market movement. To investigate loss aversion, we employ a GARCH (1.1) model to assess volatility clustering. The findings reveal heightened sensitivity to recent return shocks and persistent volatility, consistent with behavior driven by fear of loss. Additionally, overreaction tests using lagged-return regressions suggest investors responded irrationally to new information, leading to short-term reversals. Together, these results provide empirical support for behavioral finance theories and challenge traditional assumptions of rational investor behavior during systemic crises.