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Improving equity premium forecasts by incorporating structural break uncertainty


Tian, J and Zhou, Q, Improving equity premium forecasts by incorporating structural break uncertainty, Accounting and Finance pp. 1-38. ISSN 0810-5391 (2016) [Refereed Article]

Copyright Statement

Copyright 2016 AFAANZ

DOI: doi:10.1111/acfi.12240


This article compares five alternative methods for directly dealing with structural break uncertainty in forecasting the U.S. equity premium using 30 widely used bivariate and multivariate predictive regressions. We find that two recently developed methods Robust Optimal Weights on Observations and Forecast Combination across Estimation Windows outperform the conventional rolling window and postbreak estimation methods. This result indicates that very early historical information is beneficial for U.S. equity premium forecasting but should be discounted to incorporate structural break uncertainty.

Item Details

Item Type:Refereed Article
Keywords:Structural break uncertainty; Out-of-sample forecast; Equity
Research Division:Economics
Research Group:Applied economics
Research Field:Financial economics
Objective Division:Economic Framework
Objective Group:Macroeconomics
Objective Field:Macroeconomics not elsewhere classified
UTAS Author:Tian, J (Dr Jing Tian)
ID Code:112069
Year Published:2016
Web of Science® Times Cited:2
Deposited By:TSBE
Deposited On:2016-10-25
Last Modified:2018-04-05

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