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Journal of Economic Theory and Econometrics
Journal of the Korean Econometric Society
Long-Horizon Stock Return Predictability Test with A Nonlinear Nonparametric Bootstrap Method
Vol.19, No.1, March 2008, 17–48
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Ho-Jin Lee
(Department of Business Administration, Myongji University)
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Abstract
A nonparametric bootstrap procedure with an LSTAR modeling of the valuation ratio is applied to the continuously compounded real stock return and the log of the price-dividend process. The empirical distribution of the test statistics shows that the evidence for a stock return predictability weakens when we take care of nonlinearity dynamics in the regressor. We split the sample into two regimes and implement the long-horizon predictability tests. Results show that the stock return is predictable in the stationary regime, while the test statistic under the null of unpredictability is insignificant in the non-stationary regime.
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Keywords
Structural Change, Price-Dividend Ratio, Long-Horizon Regression Model, Bootstrapping, LSTAR Model (Logistic Smooth Transition Autoregressive Model) |
JEL classification codes
C22, G14 |
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