A quantile-boosting approach to forecasting gold returns

Christian Pierdzioch, Marian Risse and Sebastian Rohloff

The North American Journal of Economics and Finance, 2016, vol. 35, issue C, 38-55

Abstract: We use a quantile-boosting approach to compute out-of-sample forecasts of gold returns. The approach accounts for model uncertainty and model instability, and it allows forecasts to be computed under asymmetric loss functions. Different asymmetric loss functions represent different types of investors (optimists versus pessimists). We document how the performance of a simple trading rule varies across investor types.

Keywords: Quantile-boosting approach; Forecasting; Asymmetric loss; Gold returns (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1062940815001023
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:35:y:2016:i:c:p:38-55

DOI: 10.1016/j.najef.2015.10.015

Access Statistics for this article

The North American Journal of Economics and Finance is currently edited by Hamid Beladi

More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().