Abstract
PurposeThis paper aims to examine the performance of Islamic and conventional stocks listed at the Pakistan Stock Exchange by using both parametric and non-parametric approaches. The motivation is to do risk-return analysis of Islamic stock prices and conventional stock prices.Design/methodology/approachIt uses various measures of performance, e.g. Sharpe ratio, Treynor ratio, Jensen's alpha, beta, generalized auto-regressive conditional heteroskedasticity and stochastic dominance. Using the Karachi Meezan Index-30 (KMI-30) and the Karachi Stock Exchange Index-30 (KSE-30) as proxies for Islamic and conventional stock prices, respectively, it examines the performance of Islamic and conventional stocks. The daily data of KMI-30 and KSE-30, covering period from June 9, 2009 to June 20, 2020 are used.FindingsThe results show that the overall KMI-30 outperforms the KSE-30. The returns of the KMI-30 are greater than the KSE-30. However, the risk and volatility of the KMI-30 and KSE-30 are similar. Further, the KMI-30 has higher excess returns per unit of total risk than the KSE-30. But both indexes have similar excess returns per unit of systematic risk. Moreover, the KMI-30 returns have stochastically dominance over the KSE-30 returns. These results reveal that the Islamic index performs better than the conventional index.Practical implicationsThe findings provide several practical implications in financial and investment decisions making by investors, managers and policymakers such as strategies for asset allocation and investment. Further, in risk management, it provides guidance for allocating portfolios and managing risk. The investment in Islamic stocks may mitigate potential risk within asset portfolios.Originality/valueThis research is unique in its approach to the analysis of the performance comparison of conventional and Islamic stock by using comprehensive parametric and non-parametric estimation techniques. Such research has not been undertaken in the Pakistan's equity market since.
Subject
Economics and Econometrics,Finance,Development
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