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A Study of Portfolio Optimization Model Based on CVaR and Empirical Comparison Research

Author: AnGuoQiang
Tutor: ZhanYuanRui
School: Tianjin University
Course: Management Science and Engineering
Keywords: Value at Risk (VaR) Conditional value at risk (CVaR) Monte Carlo simulation Combinatorial optimization Efficient Frontier
CLC: F830.91
Type: Master's thesis
Year: 2007
Downloads: 322
Quote: 3
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Abstract


Research securities portfolio risk measurement and portfolio optimization theory and methods of control of financial risk , stable financial order has a very important significance . The article unfolds research is conducted in the framework of Markowitz portfolio optimization theory In this framework, the income from the portfolio selection , risk and strategy of the three angles brief introduction to the foundation of modern portfolio theory . After key research emphasis and difficulty ? Risk measure , system analysis VaR risk measure of the analytical method , historical simulation and Monte Carlo simulation method , and compare their advantages and disadvantages , and the application of modern portfolio . Uryasev and Rockafellar not coherent risk measure VaR method and its algorithm is more complex , to improve conditions VaR (CVaR) VaR . Between VaR and CVaR -depth analysis , in-depth study of the two major categories of metrics CVaR method : linear programming method and extreme value theory . On this basis , this paper focuses on VaR and CVaR based portfolio optimization model , the use of geometric methods to solve based on the the VaR constraints mean - variance model , and Mean-VaR model and can be transformed into a linear programming mean - CVaR model . Finally, by means of Matlab and Excel software , comparative empirical study of this paper creatively study the optimal portfolio and the efficient frontier of the mean - variance model , mean -VaR model and the mean -CVaR model , draw a mean -CVaR model not only has better theoretical characteristics , but also with respect to other model is more suitable for China 's stock market has important practical significance . In the course of the study also simple returns and logarithmic returns combined method and the use of Monte Carlo simulation method to simulate and predict portfolio returns . The system then the confidence level , the impact of transaction costs and capital constraints limit the efficient frontier of the mean -CVaR portfolio optimization model . This article is a National Science Foundation -funded project \Applied Research \

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