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Improving equity premium forecasts by incorporating structural break uncertainty
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.
History
Publication title
Accounting and FinancePagination
1-38ISSN
0810-5391Department/School
TSBEPublisher
Wiley-Blackwell Publishing AsiaPlace of publication
AustraliaRights statement
Copyright 2016 AFAANZRepository Status
- Restricted