Geopolitical risk and excess stock returns predictability: New evidence from a century of data
Feng Ma,
Fei Lu and
Ying Tao
Finance Research Letters, 2022, vol. 50, issue C
Abstract:
This study applies a new series of geopolitical risk historical indices developed by Caldara and Iacoviello (2022) to predict stock returns. Empirical results show that the geopolitical threats index (GPRHT) can help in predicting stock returns, especially during expansion. Combined the geopolitical indices and 14 famous macroeconomic variables can yield good out-of-sample performances from statistical and economic viewpoints. Our research provides fresh perspectives on stock return predictability in light of geopolitical risks.
Keywords: Geopolitical risks; Geopolitical threats; Excess stock returns; Portfolio performance (search for similar items in EconPapers)
Date: 2022
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/S1544612322004160
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:finlet:v:50:y:2022:i:c:s1544612322004160
DOI: 10.1016/j.frl.2022.103211
Access Statistics for this article
Finance Research Letters is currently edited by R. Gençay
More articles in Finance Research Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().