How Stable are Financial Prediction Models? Evidence from US and International Stock Market Data
AbstractThis study examines evidence of structural breaks in models of predictable components in stock returns related to state variables such as the lagged dividend yield, Treasury bill rate, term spread and default premium. We examine a large set of size-and-industry-sorted profolios of US stocks as well as 18 international stock market profolios and find systematic evidence of breaks in the vast majority of porfolios. The breakpoints most frequently identified in the US data are 1966, 1974, 1983, and 1990. The 1966 and 1974 breaks appear to have been driven by the T-bill rate and the default premium coefficients, while the 1983 break reflects changes in the coefficient on the T-bill rate and the term spread and the 1990 break was driven by the dividend yield and default premium coeffciencts. Our evidence also suggests that, while the size of the predictable component in stock returns has come down after the most recent break, many predictors continue to be significant. Although in-sample predictability of returns was lower in the 1990s than in some previous decades, it does not seem to have
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Bibliographic InfoPaper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number qt74v515fr.
Date of creation: 19 Jun 2002
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structural breaks; stock returns; financial models;
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- Todd E. Clark & Michael W. McCracken, 2009.
"Improving Forecast Accuracy By Combining Recursive And Rolling Forecasts,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(2), pages 363-395, 05.
- Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City.
- Todd E. Clark & Michael W. McCracken, 2008. "Improving forecast accuracy by combining recursive and rolling forecasts," Working Papers 2008-028, Federal Reserve Bank of St. Louis.
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