Abstract
<abstract>
<p>This study aimed to investigate the risk-return relationship, provided volatility feedback was taken into account, in the South African market. Volatility feedback, a stronger measure of volatility, was treated as an important source of asymmetry in the investigation of the risk-return relationship. This study analyzed the JSE ALSI excess returns and realized variance for the sample period from 15 October 2009 to 15 October 2019. This study modelled the novel and robust Bayesian approach in a parametric and nonparametric framework. A parametric model has modelling assumptions, such as normality, and a finite sample space. A nonparametric approach relaxes modelling assumptions and allows for an infinite sample space; thus, taking into account every possible asymmetric risk-return relationship. Given that South Africa is an emerging market, which is subject to higher levels of volatility, the presence of volatility feedback was expected to be more pronounced. However, contrary to expectations, the test results from both the parametric and nonparametric Bayesian model showed that volatility feedback had an insignificant effect in the South African market. The risk-return relationship was then investigated free from empirical distortions that resulted from volatility feedback. The parametric Bayesian model found a positive risk-return relationship, in line with traditional theoretical expectations. However, the nonparametric Bayesian model found no relationship between risk and return, in line with early South African studies. Since the nonparametric Bayesian approach is more robust than the parametric Bayesian approach, this study concluded that there is no risk-return relationship. Therefore, investors can include South Africa in their investment portfolio with higher risk countries in order to spread their risk and derive diversification benefits. In addition, risk averse investors can find a safe environment within the South African market and earn a return in accordance to their risk tolerance.</p>
</abstract>
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Development,Geography, Planning and Development
Reference27 articles.
1. Adu G, Alagidede P, Karimu A (2015) Stock return distribution in the BRICS. Rev Dev Financ 5: 98–109. https://doi.org/10.1016/j.rdf.2015.09.002
2. Bayes T (1763) An Essay towards Solving a Problem in the Doctrine of Chances by the Late Rev. Mr. Bayes, F. R. S. Communicated by Mr. Price, in a Letter to John Canton, A. M. F. R. S. Philos T (1683–1775) 53: 370–418.
3. Bekiros S, Jlassi M, Naoui K et al. (2017) The asymmetric relationship between returns and implied volatility: Evidence from global stock markets. J Financial Stab 30: 156–174. https://doi.org/10.1016/j.jfs.2017.05.006
4. Beyhaghi P, Alimo SR, Bewley TR (2018) A multiscale, asymptotically unbiased approach to uncertainty quantification in the numerical approximation of infinite time-averaged statistics. Available from: https://arXiv.org/pdf/1802.01056.pdf.
5. Brooks C (2014) Introductory Econometrics for Finance. New York: Cambridge University Press.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献