Determine the optimal portfolio weights var-stock approach And compare it with the Markowitz model
Subject Areas : Financial engineeringsayyedmohammadmahdi ahmadi 1 , hasan lotfi 2 , vali rajabi 3
1 - Department of Economics, tehran north branch, islamic azad university, tehran, iran.
2 - Department of Management and Economics, Sciences and Research Branch, Islamic Azad University, Tehran, Iran
3 - Department of Industrial Engineering, Faculty of Industrial Engineering, Amirkabir University ,Tehran, Iran.
Keywords: Stock Portfolio, Markowitz model, Value at Risk (VaR), Moving Average (EWMA),
Abstract :
Every investor is always looking for the investment portfolio that will bring him the most profit with the least risk. The standard deviation of an asset return is the amount of risk of that asset. In this study, the value-at-risk approach has been used as a measure of risk in the formation of the optimal stock portfolio. By selecting a statistical sample consisting of seven companies operating on the Tehran Stock Exchange, first the variance-covariance matrix is extracted by the moving average weighted method (EWMA) and then the Markowitz model is calculated with the aim of reducing portfolio risk against an expected return level. Portfolio performance has been achieved. Then the value-at-risk limit is added to the efficient frontier chart, and then by analyzing the sensitivity of the value-at-risk value for different values of the level of confidence and the maximum risk accepted by the investor, we show that with the risk-value approach in forming the optimal portfolio Stocks may not change the limit of the Markowitz model, or be limited, or become a point, or even disappear.
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12) Hull, J. C. (2007), Risk Management and Financial Institutions, 2nd edition,
Pearson Prentice Hall, Inc
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Swiss Federal Institute of Technology (ETH) Zurich.
14) Kaura Vinay. (2006). Portfolio Optimization Using Value at Risk, Imperial
College London
15) Kuutan Enn (2007). Portfolio Optimization Using Conditional Value-At-Risk
and Conditional Drawdown-At-Risk, University of Toronto.
16) Puelz v. Amy (nd). Value-at-Risk Based Portfolio Optimization, Southern
Methodist University, Dallas, Texas.
17) R Mansini, MG Speranza (1999). Heuristic algorithms for the portfolio
selection problem with minimum transaction lots, European Journal of Operational
Research, 114: 219–233.
18) Wei Ning Cho (2008). Robust Portfolio Optimization Using Conditional Value At
Risk, Imperial College London
