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Behavioral finance tries to make sense of financial data using models that are based on psychologically accurate assumptions about people's beliefs, preferences, and cognitive limits. I review behavioral finance approaches to understanding asset prices and trading volume, with particular emphasis on three types of models: extrapolation-based models, models of overconfident beliefs, and models of gain-loss utility inspired by prospect theory. The research to date shows that a few simple assumptions about investor psychology capture a wide range of facts about prices and volume and lead to concrete new predictions. I end by speculating about the form that a unified psychology-based model of investor behavior might take.