Application Of VaR In Risk Management Of Open Funds

Since developing institution investors and initiating value investing have been promoted in our capital market, native funds industry are developing at unprecedented speed in the past several years, especially the recent four months, and become the biggest institution investor in our capital market. Funds investment advocates that study finds value while investment makes value. The effective risk management lays the foundations for the stable operation of open funds, therefore how the native open funds management corporations control the risk and earn stable return with advanced risk measuring and controlling technique becomes an urgent-to-solve issue in theory and practice circles. This article briefly describes the risk measuring and controlling process and quantified index of open funds, and systematically expounds advanced risk measuring and controlling technique: VaR, Stress Testing, Extreme Value Theory that international financial institutions have been using and how these three complementary technique are applied in risk measuring and controlling of open funds by combining qualified analysis with quantified analysis。This article is composed of five chapters. The updated development situation of native funds industry and the background of VaR are introduced briefly. Risk controlling process and index of open funds management corporation are discussed and risk controlling index VaR is presented. The methods of computing VaR of portfolio in open funds are studied, and the merits & defects and updated development of each method are provided after the rationale of computing VaR of portfolio is introduced in chapter two. The application of VaR in notion of portfolio management and portfolio allocation is analyzed in detail in chapter three. Applying risk adjusted return on capital(RAROC) to evaluation of investment is the important investment notion. Then VaR is introduced into Markowits mean-variance model and thus the optimal solution is obtained through the model. A example of computing optimal portfolio allocation with the limitation of VaR is provided. Stress testing and extreme theory are introduced as the supplement of VaR since VaR has strict premise in chapter four and five. The application scope and effects of stress testing are proposed in the beginning and then the method of stress testing-situation simulation analysis is described and the example is provided. Extreme theory takes GDP as the superloss distribution considering the disadvantage of stress testing and the example of how to compute VaR in extreme theory is provided. Finally, the difficulty of applying VaR,stress testing and extreme theory in risk management of open funds is analyzed.