The stock-bond nexus and investors’ behavior in mature and emerging markets: Evidence from long-term historical data
Studies in Economics and Finance
ISSN: 1086-7376
Article publication date: 3 May 2019
Issue publication date: 27 July 2021
Abstract
Purpose
Portfolio construction and diversification is a prominent challenge for investors. It reflects market agents’ behavior and response to market conditions. This paper aims to investigate the stock-bond nexus in the case of two emerging and two mature markets, India, South Africa, the UK and the USA, using long-term historical monthly data.
Design/methodology/approach
To address the issue at hand, copula quantile-on-quantile regression (C-QQR) is used to model the correlation structure. Although this technique is driven by copula-based quantile regression model, it retains more flexibility and delivers more robust and accurate estimates.
Findings
Results suggest that there is substantial heterogeneity in the bond-stock returns correlation across the countries under study point to different investors’ behavior in the four markets examined. Additionally, the findings reported herein suggest that using C-QQR in portfolio management can enable the formation of tailored response strategies, adapted to the needs and preferences of investors and traders.
Originality/value
To the best of the authors’ knowledge, no previous study has addressed in a comparative setting the stock-bond nexus for the four countries used here using long-term historical data that cover the periods 1920:08-2017:02, 1910:01-2017:02, 1933:01-2017:02 and 1791:09-2017:02 for India, South Africa, the UK and the USA, respectively.
Keywords
Acknowledgements
The authors gratefully acknowledge the useful comments and constructive suggestions by three anonymous referees that helped improve the paper. The usual disclaimer applies.
Citation
Selmi, R., Gupta, R., Kollias, C. and Papadamou, S. (2021), "The stock-bond nexus and investors’ behavior in mature and emerging markets: Evidence from long-term historical data", Studies in Economics and Finance, Vol. 38 No. 3, pp. 562-582. https://doi.org/10.1108/SEF-08-2017-0224
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited