-horizon forecasts are well-described by adaptive learning, which delivers convergence to RE equilibrium, while short-horizon forecasts …

that maximize (risk-adjusted) expected profits. A real-time learning formulation yields endogenous switching between … equilibria. We demonstrate that a real-time learning version of the model, calibrated to U.S. stock data, is capable of …

This chapter provides a survey of the recent work on learning in the context of macroeconomics. Learning has several … roles. First, it provides a boundedly rational model of how rational expectations can be achieved. Secondly, learning acts … as a selection device in models with multiple REE (rational expectations equilibria). Third, the learning dynamics …

-horizon forecasts are well-described by adaptive learning, which delivers convergence to RE equilibrium, while short-horizon forecasts …

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as … several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes …

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as … mechanisms through which learning impacts stock prices: occasional shocks may lead agents to lower their risk estimate and …