53 Pages Posted: 4 Apr 2016 Last revised: 2 Jun 2017
Date Written: May 31, 2017
Neely et al. (2014) have recently demonstrated how to efficiently combine information from a set of popular technical indicators together with the standard Goyal and Welch (2008) predictor variables widely used in the equity premium forecasting literature to improve out-of-sample forecasts of the equity premium using a small number of principal components. We show that forecasts of the equity premium can be further improved by, first, incorporating broader macroeconomic data into the information set, second, improving the selection of the most relevant factors and combining the most relevant factors by means of a forecast combination regression, and third, imposing theoretically motivated positivity constraints on the forecasts of the equity premium. We find that in particular our proposed forecast combination approach, which combines forecasts of the most relevant Neely et al. (2014) and macroeconomic factors and further imposes positivity constraints on the equity premium forecasts, generates statistically significant and economically sizeable improvements over the best performing model of Neely et al. (2014).
Keywords: Equity premium predictability, Factor models, Macroeconomic variables, Adaptive Lasso, Sign restrictions, Forecast combination, Asset allocation
JEL Classification: G12, G17, C53, E44
Suggested Citation: Suggested Citation
Buncic, Daniel and Tischhauser, Martin, Macroeconomic Factors and Equity Premium Predictability (May 31, 2017). Available at SSRN: https://ssrn.com/abstract=2757155