Simple Forecasts and Paradigm Shifts

52 Pages Posted: 5 Oct 2003 Last revised: 18 Sep 2009

See all articles by Harrison G. Hong

Harrison G. Hong

Columbia University, Graduate School of Arts and Sciences, Department of Economics; National Bureau of Economic Research (NBER)

Jeremy C. Stein

Harvard University - Department of Economics; National Bureau of Economic Research (NBER)

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Date Written: October 2003

Abstract

We study the implications of learning in an environment where the true model of the world is a multivariate one, but where agents update only over the class of simple univariate models. If a particular simple model does a poor job of forecasting over a period of time, it is eventually discarded in favor of an alternative yet equally simple model that would have done better over the same period. This theory makes several distinctive predictions, which, for concreteness, we develop in a stock-market setting. For example, starting with symmetric and homoskedastic fundamentals, the theory yields forecastable variation in the size of the value/glamour differential, in volatility, and in the skewness of returns. Some of these features mirror familiar accounts of stock-price bubbles.

Suggested Citation

Hong, Harrison G. and Stein, Jeremy C., Simple Forecasts and Paradigm Shifts (October 2003). NBER Working Paper No. w10013. Available at SSRN: https://ssrn.com/abstract=453807

Harrison G. Hong

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

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Jeremy C. Stein (Contact Author)

Harvard University - Department of Economics ( email )

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HOME PAGE: http://post.economics.harvard.edu/faculty/stein/stein.html

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