Open AccessMarkowitz Theory in Portfolio Optimization for Heavy Tailed Assets
Author(s) -
Wong Ghee Ching,
Che Mohd Imran Che Taib
Publication year - 2019
Publication title -
universiti malaysia terengganu journal of undergraduate research
Language(s) - English
Resource type - Journals
ISSN - 2637-1138
DOI - 10.46754/umtjur.v1i3.74
Subject(s) - portfolio , portfolio optimization , post modern portfolio theory , modern portfolio theory , efficient frontier , rate of return on a portfolio , black–litterman model , econometrics , variance (accounting) , economics , index (typography) , order (exchange) , actuarial science , financial economics , replicating portfolio , computer science , finance , accounting , world wide web
This paper aims at solving an optimization problem in the presence of heavy tail behavior of financial assets. The question of minimizing risk subjected to a certain expected return or maximizing return for a given expected risk are two objective functions to be solved using Markowitz model. The Markowitz based strategies namely the mean variance portfolio, minimum variance portfolio and equally weighted portfolio are proposed in conjunction with mean and variance analysis of the portfolio. The historical prices of stocks traded at Bursa Malaysia are used for empirical analysis. We employed CAPM in order to investigate the performance of the Markowitz model which was benchmarked with risk adjusted KLSE Composite Index. We performed a backtesting study of portfolio optimization techniques defined under modern portfolio theory in order to find the optimal portfolio. Our findings showed that the mean variance portfolio outperformed the other two strategies in terms of performance of investment for heavy tailed assets.