Research On Information Entropy Methods In Risk Measure

Under the influence of economic globalization and financial integration, the investment market of various countries has developed swiftly and violently, the investment risk is also quietly rising at the same time. Investors always expect to obtain stable return and avoid unnecessary risk. Therefore, how to measure the investment risk accurately by using of a reasonable way is not only an issue concerned investors, by but also an important subject of modern finance.In this thesis, we survey some a series of method of risk measure under this background; especially emphasize the information entropy method in recent years. The full text is divided into five chapters:In Chapter1, we first introduce the background of risk measure, research situation and mainly results and organization of this paper.In Chapter2, we review some of the classic methods of risk measure, including their development process and strengths and weaknesses.In Chapter3, we introduce the entropy of origin and development, the definition and property of information entropy and maximum entropy and minimal relative entropy principle. All of this provides necessary theoretical support for the next chapter.The4th Chapter is the focus of this thesis. We give several risk measurement model with respect to information entropy and analysis respectively the characteristics and application range in theory.The5th Chapter adopts the method of empirical analysis, more precise, we select50good stocks as the sample, and compare the similarities and differences of the traditional risk measure model and entropy model by using of the MATLAB programming method. Finally it is concluded that the entropy of the advantages of the risk measure model. The last chapter is the summary of this paper and outlook for the future work.