本文選題：隱馬爾可夫模型 + VaR風險價值　； 參考：《合肥工業(yè)大學》2013年碩士論文

【摘要】：新世紀特別是2008年世界金融危機爆發(fā)以來，國際、國內金融市場都發(fā)生了深刻的變革，金融市場風險明顯增大，分析金融波動特征和度量金融市場風險對投資與監(jiān)管都具有重要的意義。VaR(Value-at-Risk)方法以其高度的綜合概括能力，為投資者提供了一個直觀、全面的風險量化指標，，目前已成為世界主流的風險測度方法。本文主要針對金融數據所呈現(xiàn)的尖峰厚尾、波動持續(xù)、結構轉變等特征，探討了金融市場風險度量的VaR模型的改進方法與應用。 首先對本文的研究背景及意義、VaR模型在國內外的研究概況進行概述，并提出了本文的主要內容。然后介紹了隱馬爾可夫模型的基本概念與算法，指出其在異常狀態(tài)識別上的應用。緊接著闡述了VaR的基本原理與計算方法，指出常用的ARCH模型族估算波動率方法的不足，在此基礎上提出了本文模型：HMM-ARMA-GARCH模型，用隱馬爾可夫模型的狀態(tài)變量來描述金融市場的正常波動狀態(tài)與異常波動狀態(tài)，同時不可觀測的狀態(tài)變量能夠對波動的集聚現(xiàn)象給出很好的解釋。對不同的狀態(tài)數據分別建立ARMA-GARCH模型來估算波動率，同時給出VaR的具體計算方法。最后對上證企債指數進行實證分析，采用Kupiec失敗頻率檢驗法對VaR的準確性進行檢驗，并與傳統(tǒng)的ARMA-GARCH模型的估算效果進行比較。實證結果表明基于本文模型的VaR計算方法具有較好的估計效果，且能夠有效的降低GARCH模型高估波動持續(xù)性的現(xiàn)象。
[Abstract]:In the new century, especially since the outbreak of the world financial crisis in 2008, profound changes have taken place in the international and domestic financial markets, and the risks in the financial markets have obviously increased. It is important to analyze the characteristics of financial volatility and to measure financial market risk for investment and supervision. The VaR (Value-at-Risk) method, with its high comprehensive generalization ability, provides an intuitive and comprehensive risk quantification index for investors. At present, it has become the mainstream risk measurement method in the world. Aiming at the characteristics of financial data, such as peak and thick tail, persistent fluctuation and structural transformation, this paper discusses the improved method and application of VaR model for financial market risk measurement. Firstly, the research background and significance of this paper are summarized, and the main contents of this paper are put forward. Then the basic concept and algorithm of hidden Markov model are introduced, and its application in abnormal state recognition is pointed out. Then, the basic principle and calculation method of VaR are expounded, and the shortcomings of the common arch model family are pointed out. On this basis, the model of this paper is proposed, which is the: HMM-ARMA-GARCH model. The state variables of hidden Markov model are used to describe the normal volatility and abnormal volatility in the financial market. At the same time, the unobservable state variables can give a good explanation for the agglomeration of volatility. The ARMA-GARCH model is established for different state data to estimate volatility, and the specific calculation method of VaR is given. Finally, the empirical analysis on the debt index of Shanghai stock market is carried out, and the accuracy of VaR is tested by using the Kupiec failure frequency test method, and compared with the estimation effect of the traditional ARMA-GARCH model. The empirical results show that the VaR calculation method based on this model has better estimation effect and can effectively reduce the phenomenon of overestimating volatility persistence in GARCH model.
【學位授予單位】：合肥工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F830.91;F224;O211.62

【參考文獻】

相關期刊論文 前10條

1 詹原瑞;劉家鵬;蘇濤;;基于馬爾科夫機制轉換CAPM的VaR模型研究[J];電子科技大學學報(社科版);2008年03期

2 孫金麗,張世英;具有結構轉換的GARCH模型及其在中國股市中的應用[J];系統(tǒng)工程;2003年06期

3 鄭文通;金融風險管理的VAR方法及其應用[J];國際金融研究;1997年09期

4 王春峰,李剛;基于分布擬合法的VaR估計[J];管理工程學報;2002年04期

5 劉小茂,李楚霖,王建華;風險資產組合的均值—CVaR有效前沿(Ⅰ)[J];管理工程學報;2003年01期

6 惠軍;朱翠;;證券投資基金市場的ARMA-ARCH類模型分析[J];合肥工業(yè)大學學報(自然科學版);2010年07期

7 譚常春;張勇;張虎;;基于不同誤差分布下ARMA-GARCH模型的國債指數實證研究[J];合肥學院學報(自然科學版);2011年03期

8 瞿慧;肖斌卿;;基于馬爾科夫狀態(tài)轉移模型的股指收益率研究[J];管理科學;2011年05期

9 王春峰,萬海輝,李剛;基于MCMC的金融市場風險VaR的估計[J];管理科學學報;2000年02期

10 劉宇飛;VaR模型及其在金融監(jiān)管中的應用[J];經濟科學;1999年01期

本文編號：2060268