本文選題：VaR + Expected�。� 參考：《南昌大學(xué)》2014年碩士論文

【摘要】：本文主要是討論風(fēng)險(xiǎn)度量新方法ES的基本原理；基于ARMA-GARCH模型展開對(duì)我國創(chuàng)業(yè)板市場(chǎng)日收盤價(jià)對(duì)數(shù)收益率的市場(chǎng)風(fēng)險(xiǎn)實(shí)證分析，計(jì)算其VaR值和ES值來度量創(chuàng)業(yè)板指數(shù)的市場(chǎng)風(fēng)險(xiǎn)；此外，也運(yùn)用向量自回歸模型探討創(chuàng)業(yè)板和中小板的相互影響，深度分析創(chuàng)業(yè)板的風(fēng)險(xiǎn)因素。全文共分5章。 第一章介紹本文研究主要內(nèi)容的背景、意義和方法，簡要敘述VaR和ES相關(guān)歷史文獻(xiàn)。 第二章主要介紹ES基本原理。采用資產(chǎn)組合損失變量描述風(fēng)險(xiǎn)，并基于損失分布的-（上）分位數(shù)給出“期望巨額損失值”ES（Expected Shortfall）和“條件風(fēng)險(xiǎn)價(jià)值”CVaR（Conditional Value at Risk）的定義。在一般損失分布下，通過直接計(jì)算說明了任一資產(chǎn)組合損失變量的“期望巨額損失值”ES的定義與-（上）分位數(shù)的選取無關(guān)；而且也通過直接計(jì)算證明了ES與CVaR兩者的等價(jià)關(guān)系；進(jìn)而通過構(gòu)造出ES的概率測(cè)度族表示證明了ES是一致性風(fēng)險(xiǎn)度量方法。 第三章基于ARMA-GARCH模型，運(yùn)用風(fēng)險(xiǎn)度量的VaR和ES方法對(duì)創(chuàng)業(yè)板指數(shù)（樣本：2010.6.1-2014.2.1）的市場(chǎng)風(fēng)險(xiǎn)進(jìn)行實(shí)證分析，，包括VaR、ES的計(jì)算問題、比較分析等。首先對(duì)創(chuàng)業(yè)板塊日收盤指數(shù)之間的自然對(duì)數(shù)收益率進(jìn)行基本統(tǒng)計(jì)分析，發(fā)現(xiàn)序列的分布存在厚尾的特征；運(yùn)用AIC+SC準(zhǔn)則確定各模型的滯后階數(shù)。對(duì)各模型的參數(shù)進(jìn)行估計(jì)，得到殘差序列，進(jìn)一步得到殘差序列的VaR值，并根據(jù)模型的數(shù)學(xué)表達(dá)式得到最終的VaR值和ES值。最后利用失敗率檢驗(yàn)法，對(duì)模型進(jìn)行檢驗(yàn)。實(shí)證的結(jié)果表明，ES在VaR估計(jì)失敗時(shí)，能比較準(zhǔn)確地估計(jì)例外情形的實(shí)際損失，即ES可以用來彌補(bǔ)VaR模型的缺點(diǎn)，ES是比VaR更加穩(wěn)健和保守的風(fēng)險(xiǎn)度量方法。 第四章運(yùn)用VAR（向量自回歸）模型，研究創(chuàng)業(yè)板收盤指數(shù)和中小板收盤指數(shù)的相互影響。通過協(xié)整以及格蘭杰因果檢驗(yàn)，分析創(chuàng)業(yè)板和中小板之間的內(nèi)在關(guān)系，尋找影響創(chuàng)業(yè)板風(fēng)險(xiǎn)的外部因素。結(jié)果表明，它們的波動(dòng)性是比較一致的；中小板和創(chuàng)業(yè)板之間不存在長期均衡關(guān)系。研究結(jié)果進(jìn)一步表明，創(chuàng)業(yè)板對(duì)中小板的影響要大一些。 第五章是對(duì)全文進(jìn)行的總結(jié)并指出了文中的不足以及對(duì)今后研究方向的展望。
[Abstract]:This paper mainly discusses the basic principle of the new risk measurement method es, analyzes the market risk based on ARMA-GARCH model, calculates the VaR value and es value to measure the market risk of gem.In addition, the vector autoregressive model is used to study the interaction between the gem and the small and medium-sized board, and the risk factors of the gem are analyzed in depth.The full text is divided into five chapters.The first chapter introduces the background, significance and methods of the research, and briefly describes the historical documents related to VaR and es.The second chapter mainly introduces the basic principle of es.The risk is described by portfolio loss variables, and the definitions of "ES(Expected short fallings" and "CVaR(Conditional Value at risk" are given based on the-(upper) quantiles of the loss distribution.Under the general loss distribution, the definition of "expected huge loss value" es of any portfolio loss variable is directly calculated, which is independent of the selection of-(upper) quantiles.Furthermore, the equivalent relation between es and CVaR is proved by direct calculation, and then es is proved to be a consistent risk measure by constructing the representation of the probability measure family of es.The third chapter is based on the ARMA-GARCH model, using the VaR and es methods of risk measurement to analyze the market risk of gem index (sample:: 2010.6.1-2014.2.1), including the calculation problem and comparative analysis.Firstly, the natural logarithmic return rate between the daily closing index of entrepreneurial plate is analyzed, and it is found that the distribution of the sequence has the characteristic of thick tail, and the lag order of each model is determined by using AIC SC criterion.The parameters of each model are estimated and the residual sequence is obtained. The VaR value of the residual sequence is further obtained and the final VaR value and es value are obtained according to the mathematical expression of the model.Finally, the failure rate test method is used to test the model.The empirical results show that when the VaR estimation fails, it can accurately estimate the actual loss of exceptional cases, that is, es can be used to compensate for the shortcomings of VaR model and that es is a more robust and conservative risk measurement method than VaR.The fourth chapter studies the interaction between the gem closing index and the small and medium-sized board closing index by using VAR (vector autoregressive) model.Through cointegration and Granger causality test, this paper analyzes the internal relationship between gem and small and medium-sized board, and finds out the external factors that affect the risk of gem.The results show that their volatility is consistent, and there is no long-term equilibrium relationship between the small and medium-sized board and the growth enterprise board.The results further show that the gem has a greater impact on the small and medium-sized boards.The fifth chapter is a summary of the full text and points out the shortcomings of the paper and prospects for future research.
【學(xué)位授予單位】：南昌大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F224;F832.51

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