Evans, George W.

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https://hdl.handle.net/1794/3690

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Browsing Evans, George W. by Subject "Asset pricing"

Now showing 1 - 3 of 3
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    Asset Return Dynamics and Learning
    (University of Oregon, Dept of Economics, 2006-11-13) Branch, William A.; Evans, George W., 1949-
    This paper advocates a theory of expectation formation that incorporates many of the central motivations of behavioral finance theory while retaining much of the discipline of the rational expectations approach. We provide a framework in which agents, in an asset pricing model, underparameterize their forecasting model in a spirit similar to Hong, Stein, and Yu (2005) and Barberis, Shleifer, and Vishny (1998), except that the parameters of the forecasting model, and the choice of predictor, are determined jointly in equilibrium. We show that multiple equilibria can exist even if agents choose only models that maximize (risk-adjusted) expected profits. A real-time learning formulation yields endogenous switching between equilibria. We demonstrate that a realtime learning version of the model, calibrated to U.S. stock data, is capable of reproducing many of the salient empirical regularities in excess return dynamics such as under/overreaction, persistence, and volatility clustering.
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    Learning about Risk and Return: A Simple Model of Bubbles and Crashes
    (University of Oregon, Dept of Economics, 2008-01-31) Branch, William A.; Evans, George W., 1949-
    This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they generate forecasts of the conditional variance of a stock’s return. Recursive updating of the conditional variance and expected return implies two mechanisms through which learning impacts stock prices: occasional shocks may lead agents to lower their risk estimate and increase their expected return, thereby triggering a bubble; along a bubble path recursive estimates of risk will increase and crash the bubble.
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    Learning and Macroeconomics
    (University of Oregon, Dept of Economics, 2008-07-11) Honkapohja, Seppo, 1951-; Evans, George W., 1949-
    Expectations play a central role in modern macroeconomic theories. The econometric learning approach models economic agents as forming expectations by estimating and updating forecasting models in real time. The learning approach provides a stability test for rational expectations and a selection criterion in models with multiple equilibria. In addition, learning provides new dynamics if older data is discounted, models are misspecified or agents choose between competing models. This paper describes the E-stability principle and the stochastic approximation tools used to assess equilibria under learning. Applications of learning to a number of areas are reviewed, including the design of monetary and fiscal policy, business cycles, self-fulfilling prophecies, hyperinflation, liquidity traps, and asset prices.