Applications of Quadratic Programming and Genetic Algorithm To Portfolio Optimization
ZHOU, LILI (2009) Applications of Quadratic Programming and Genetic Algorithm To Portfolio Optimization. [Dissertation (University of Nottingham only)] (Unpublished)
Portfolio selection and optimization problems in the financial world have gained a lot of attention. The mean-variance model of the Markowitz (1959) has been widely applied to solve these problems, which considers the optimization process as an efficient diversification to obtain the optimal relation between the expected return and risk (variance) of the structured portfolio. Portfolios of the lowest joint risk at a desired return or those of the maximal return at a certain risk are named efficient portfolios. Varying the desired portfolio return (or risk) provides opportunities to create the efficient frontier in a risk-return coordinate based on various efficient portfolios. Efficient frontiers give investors visible directions of what minimal risk matches their expected return or how great return they are able to reach at a level of risk, and therefore indicate the best way of investing money.
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