Meligkotsidou, Loukia and Panopoulou, Ekaterini and Vrontos, Ioannis D and Vrontos, Spyridon D (2014) A Quantile Regression Approach to Equity Premium Prediction. Journal of Forecasting, 33 (7). pp. 558-576. DOI https://doi.org/10.1002/for.2312
Meligkotsidou, Loukia and Panopoulou, Ekaterini and Vrontos, Ioannis D and Vrontos, Spyridon D (2014) A Quantile Regression Approach to Equity Premium Prediction. Journal of Forecasting, 33 (7). pp. 558-576. DOI https://doi.org/10.1002/for.2312
Meligkotsidou, Loukia and Panopoulou, Ekaterini and Vrontos, Ioannis D and Vrontos, Spyridon D (2014) A Quantile Regression Approach to Equity Premium Prediction. Journal of Forecasting, 33 (7). pp. 558-576. DOI https://doi.org/10.1002/for.2312
Abstract
<jats:title>ABSTRACT</jats:title><jats:p>We propose a quantile regression approach to equity premium forecasting. Robust point forecasts are generated from a set of quantile forecasts using both fixed and time‐varying weighting schemes, thereby exploiting the entire distributional information associated with each predictor. Further gains are achieved by incorporating the forecast combination methodology into our quantile regression setting. Our approach using a time‐varying weighting scheme delivers statistically and economically significant out‐of‐sample forecasts relative to both the historical average benchmark and the combined predictive mean regression modeling approach. Copyright © 2014 John Wiley & Sons, Ltd.</jats:p>
Item Type: | Article |
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Uncontrolled Keywords: | equity premium; forecast combination; predictive quantile regression; robust point forecasts; time-varying weights |
Subjects: | Q Science > QA Mathematics |
Divisions: | Faculty of Science and Health Faculty of Social Sciences Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 12 Nov 2014 20:05 |
Last Modified: | 30 Oct 2024 20:32 |
URI: | http://repository.essex.ac.uk/id/eprint/11558 |
Available files
Filename: MPVV.pdf