PORTFOLIO OPTIMIZATION WITH MEAN-VARIANCE & MEAN-CVAR: EVIDENCE FROM PAKISTAN STOCK MARKET

Abstract

The stock market in any country plays a significant role in economic development through saving mobilization and providing diversification opportunities. The investors and wealth managers always looked for those securities, investment to which leads towards maximum returns. The Markowitz portfolio optimization model is based on risk and reward trade off where the returns are measured with Mean and Variance is used as proxy of risk. The framework is criticized due to its normality of returns assumption and in case of non-elliptical distribution the optimization results may lead towards suboptimal portfolios. In emerging markets, returns are attributed to high volatility, low liquidity and increased market concentration. Such volatile phenomena signify the presence of downside risk. The expected shortfall or CVaR has reported ability to measure loss beyond VaR and regarded as coherent risk measure. This study investigated the impact on asset pricing of PSX stocks with Mean Variance and Mean-CVaR model by analyzing KSE100 index stocks for the time period 2009-2018. The empirical findings of the in sample performance of Mean-CVaR optimization for non-normal stocks indicated higher Sharpe ratio while for normal stocks return data portfolio selection and optimization with MV model SR is higher. The results of this study are useful for the investors and fund managers to understand PSX behavior and in selection of optimal portfolios.