Improving Equity Premium Forecasts by Incorporating Structural Break Uncertainty

38 Pages Posted: 23 Oct 2018

See all articles by Jing Tian

Jing Tian

University of Tasmania; Financial Research Network (FIRN)

Qing Zhou

Department of Applied Finance and Actuarial Studies, Macquarie University

Date Written: November 2018

Abstract

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.

Keywords: Structural break uncertainty, Out‐of‐sample forecast, Equity premium

Suggested Citation

Tian, Jing and Zhou, Qing, Improving Equity Premium Forecasts by Incorporating Structural Break Uncertainty (November 2018). Accounting & Finance, Vol. 58, pp. 619-656, 2018, Available at SSRN: https://ssrn.com/abstract=3271197 or http://dx.doi.org/10.1111/acfi.12240

Jing Tian (Contact Author)

University of Tasmania ( email )

French Street
Sandy Bay
Tasmania, 7250
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Qing Zhou

Department of Applied Finance and Actuarial Studies, Macquarie University ( email )

Sydney, NSW
Australia

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