• Medientyp: E-Book
  • Titel: Model-free and Model-based Learning as Joint Drivers of Investor Behavior
  • Beteiligte: Barberis, Nicholas [Verfasser:in]; Jin, Lawrence J. [Verfasser:in]
  • Körperschaft: National Bureau of Economic Research
  • Erschienen: Cambridge, Mass: National Bureau of Economic Research, March 2023
  • Erschienen in: NBER working paper series ; no. w31081
  • Umfang: 1 Online-Ressource; illustrations (black and white)
  • Sprache: Englisch
  • Schlagwörter: Anlageverhalten ; Meinung ; Lernprozess ; Verhaltensökonomik ; Behavioral Microeconomics: Underlying Principles ; Behavioral Finance: Underlying Principles ; Portfolio Choice; Investment Decisions ; Arbeitspapier ; Graue Literatur
  • Reproduktionsnotiz: Hardcopy version available to institutional subscribers
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  • Beschreibung: 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