Skip to main content

A Quantile Regression Approach to Equity Premium Prediction

Meligkotsidou, Loukia, Panopoulou, Ekaterini, Vrontos, Ioannis D., Vrontos, Spyridon D. (2014) A Quantile Regression Approach to Equity Premium Prediction. Journal of Forecasting, 33 (7). pp. 558-576. ISSN 0277-6693. E-ISSN 1099-131X. (doi:10.1002/for.2312) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:43020)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1002/for.2312

Abstract

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.

Item Type: Article
DOI/Identification number: 10.1002/for.2312
Uncontrolled keywords: equity premium; forecast combination; predictive quantile regression; robust point forecasts; time-varying weights
Subjects: H Social Sciences > HG Finance
Divisions: Divisions > Kent Business School - Division > Kent Business School (do not use)
Depositing User: Ekaterini Panopoulou
Date Deposited: 19 Sep 2014 19:20 UTC
Last Modified: 17 Aug 2022 10:57 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/43020 (The current URI for this page, for reference purposes)

University of Kent Author Information

Panopoulou, Ekaterini.

Creator's ORCID: https://orcid.org/0000-0001-5080-9965
CReDIT Contributor Roles:
  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.