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Model-free and Model-based Learning as Joint Drivers of Investor Behavior

出版	National Bureau of Economic Research, 2023
URL	http://books.google.com.hk/books?id=N2DczwEACAAJ&hl=&source=gbs_api

註釋In the past decade, researchers in psychology and neuroscience studying human decision-making have increasingly adopted a framework that combines two systems, namely "model-free" and "model-based" learning. We import this framework into a simple financial setting, study its properties, and use it to account for a range of facts: facts about investor behavior, such as extrapolative demand and experience effects; facts about beliefs, such as overreaction in beliefs and the relationship between beliefs and stock market allocations; and facts about asset prices, such as excess volatility. More broadly, the framework offers a way of thinking about individual behavior that is grounded in recent evidence on the computations that the brain undertakes when estimating the value of a course of action.