本文關(guān)鍵詞：基于Copula函數(shù)-Asymmetric Laplace分布的金融市場(chǎng)風(fēng)險(xiǎn)度量與套期保值研究　出處：《華中科技大學(xué)》2013年博士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 金融市場(chǎng)風(fēng)險(xiǎn) 金融市場(chǎng)風(fēng)險(xiǎn)度量 套期保值 Copula函數(shù) VaR

【摘要】：隨著金融全球一體化的發(fā)展，金融市場(chǎng)的復(fù)雜程度日益提高，防范金融風(fēng)險(xiǎn)已成為全社會(huì)的共識(shí)。加強(qiáng)金融系統(tǒng)風(fēng)險(xiǎn)防范和管理能力，提高市場(chǎng)轉(zhuǎn)移及消化吸收風(fēng)險(xiǎn)的能力，將是我國(guó)金融市場(chǎng)健康成長(zhǎng)和發(fā)展的重要保障。金融秩序和金融運(yùn)行環(huán)境的不斷改變，金融風(fēng)險(xiǎn)的產(chǎn)生、傳播、控制與管理等都日趨復(fù)雜，對(duì)金融市場(chǎng)風(fēng)險(xiǎn)的度量與管理的研究也更加重要和復(fù)雜。金融市場(chǎng)風(fēng)險(xiǎn)是最常見(jiàn)也是我國(guó)金融機(jī)構(gòu)面臨的主要風(fēng)險(xiǎn)，但是對(duì)其的研究，一些傳統(tǒng)的基于正態(tài)、線(xiàn)性或波動(dòng)性對(duì)稱(chēng)等模型的研究已不再適用，很難充分地捕獲市場(chǎng)風(fēng)險(xiǎn)信息。這就需要不斷探索研究，給出更多適應(yīng)現(xiàn)階段風(fēng)險(xiǎn)管理要求的理論模型研究及實(shí)證研究。 本文在分析現(xiàn)代金融風(fēng)險(xiǎn)管理理論的基礎(chǔ)上，總結(jié)了市場(chǎng)風(fēng)險(xiǎn)度量及期貨套期保值等方面的研究，指出了現(xiàn)有研究的不足，針對(duì)金融市場(chǎng)風(fēng)險(xiǎn)的復(fù)雜性，建立了基于非正態(tài)分布方法及非線(xiàn)性相關(guān)性模型的風(fēng)險(xiǎn)度量模型和套期保值策略模型，對(duì)金融市場(chǎng)風(fēng)險(xiǎn)的度量與套期保值進(jìn)行了研究。主要從以下四個(gè)方面展開(kāi)了主體部分的研究： （1）本文建立了基于Asymmetric Laplace（AL）分布的市場(chǎng)風(fēng)險(xiǎn)VaR與CVaR的度量模型。構(gòu)建了市場(chǎng)風(fēng)險(xiǎn)VaR和CVaR度量的AL參數(shù)法和AL-MC法，并進(jìn)行了比較研究。選取上證指數(shù)、日經(jīng)225指數(shù)及SP500指數(shù)為研究對(duì)象，結(jié)合各股市的風(fēng)險(xiǎn)特征，給出了VaR和CVaR度量及其返回檢驗(yàn)和準(zhǔn)確性評(píng)價(jià)。結(jié)果表明，基于AL分布的風(fēng)險(xiǎn)度量模型能更好刻畫(huà)市場(chǎng)風(fēng)險(xiǎn)特征，能很好地度量市場(chǎng)風(fēng)險(xiǎn)。 （2）本文建立了動(dòng)態(tài)風(fēng)險(xiǎn)VaR和CVaR度量的ARMA-GJR-AL模型。從相關(guān)性、波動(dòng)性及殘差分布特征三方面考慮，研究了基于ARMA-GJR-AL模型的動(dòng)態(tài)風(fēng)險(xiǎn)VaR和CVaR的度量。通過(guò)實(shí)證研究，給出了上海股市與紐約股市的市場(chǎng)風(fēng)險(xiǎn)預(yù)測(cè)及準(zhǔn)確性檢驗(yàn)，，研究了模型的有效性。結(jié)果表明，基于AL分布的動(dòng)態(tài)風(fēng)險(xiǎn)度量模型更具合理性和適用性，能有效地度量風(fēng)險(xiǎn)。 （3）本文運(yùn)用Copula函數(shù)技術(shù)來(lái)描述資產(chǎn)間的相關(guān)性結(jié)構(gòu)，建立了金融資產(chǎn)組合的市場(chǎng)風(fēng)險(xiǎn)VaR和CVaR的度量和分配的Copula-AL模型，并對(duì)常用的基于多元統(tǒng)計(jì)分布的度量方法及基于OLS模型的風(fēng)險(xiǎn)分配方法進(jìn)行了比較研究。選取上證指數(shù)和深圳成指的組合為例，計(jì)算了組合風(fēng)險(xiǎn)及其分配。結(jié)果表明，基于t-Copula-AL模型的VaR、CVaR法計(jì)算簡(jiǎn)單準(zhǔn)確，且能方便地進(jìn)行風(fēng)險(xiǎn)分配。 （4）本文采用參數(shù)和非參數(shù)分布法來(lái)刻畫(huà)邊際分布特征，結(jié)合Copula函數(shù)技術(shù)來(lái)描述期現(xiàn)市場(chǎng)間的相關(guān)性，以CVaR最小化為目標(biāo)函數(shù)，建立了基于靜態(tài)和動(dòng)態(tài)Copula-CVaR的最優(yōu)套保比率度量模型，并對(duì)各模型進(jìn)行了比較研究。以滬深300指數(shù)現(xiàn)貨和期貨為研究對(duì)象，建立了靜態(tài)和動(dòng)態(tài)Copula-CVaR模型及OLS模型，在給定套保期限內(nèi)，分析了各模型的套保費(fèi)用，并給出了修正成本套保效率的比較分析。實(shí)證結(jié)果表明，考慮套保費(fèi)用時(shí)，應(yīng)選擇簡(jiǎn)單易行的靜態(tài)套保策略，即使市場(chǎng)條件相同，也應(yīng)據(jù)自身的費(fèi)用情況選擇最優(yōu)套保策略。 本文的研究促進(jìn)了金融市場(chǎng)風(fēng)險(xiǎn)度量、期貨套期保值、AL分布及Copula函數(shù)理論等方面的研究，具有很好的理論意義，同時(shí)對(duì)投資決策、經(jīng)濟(jì)資本管理及風(fēng)險(xiǎn)管理等實(shí)踐活動(dòng)也起到很好的幫助和借鑒作用。
[Abstract]:With the development of global financial integration, the complexity of the financial market is increasing, the prevention of financial risks has become the consensus of the whole society. To strengthen the financial system risk prevention and management ability, improve the ability of digestion and absorption and transfer market risk, will be our country financial market an important guarantee for the healthy growth and development of the constantly changing financial order and. The financial environment, financial risk, communication, control and management are becoming more and more complex, the research on financial market risk measurement and management is more important and complex. Financial market risk is the most common major risks facing China's financial institutions, but the research, based on the traditional normal the study of linear or volatility symmetry model is no longer applicable, it is difficult to fully capture the market risk information. This requires continuous exploration and research, give more suitable at this stage of the wind The theoretical model research and Empirical Study of risk management requirements.
Based on the analysis of modern financial risk management theory, summarizes the research of market risk measurement and Futures Hedging etc., points out the shortcomings of existing studies, aiming at the complexity of financial market risk, establish the risk of non normal distribution method and nonlinear correlation model measurement model and hedging strategy based on the model of the measure of financial market risk and hedging are studied. Mainly from the following four aspects of the research of the main part:
(1) is established in this paper based on Asymmetric Laplace (AL) model to measure market risk VaR and CVaR distribution. The construction parameters of the AL method and AL-MC method of VaR and CVaR to measure market risk, and a comparative study. Select the Shanghai index, Nikkei 225 index and SP500 index as the research object, combined with the characteristics of the risk the stock market, given the VaR and CVaR measure and return test and evaluation. The results show that the risk distribution of AL metric model can better describe the market risk based on the features, can be a good measure of market risk.
(2) this paper establishes the ARMA-GJR-AL model of dynamic risk VaR and CVaR metrics. From the correlation, volatility and residual distribution characteristics of three aspects, the research of dynamic risk measures of VaR and CVaR based on the ARMA-GJR-AL model. Through empirical research, market risk prediction accuracy and gives the Shanghai stock market and New York stock market test, research the validity of the model. The results show that the dynamic risk measurement model of AL distribution is more reasonable and based on the application, can effectively measure the risk.
(3) this paper uses the Copula function to describe the correlation between assets structure and technology, established the Copula-AL model to measure the market risk of CVaR and VaR combination of financial assets and distribution, and the measurement methods of multivariate statistical distribution and risk allocation method based on OLS model are studied based on the commonly used combination of Shanghai Composite Index and. Shenzhen stock market as an example, the calculation of portfolio risk and distribution. The results show that the t-Copula-AL model based on VaR, the CVaR method is simple and accurate, and can carry out risk distribution conveniently.
(4) this paper uses parametric and non parametric distribution method to describe the marginal distribution characteristics, combined with the Copula function to describe the correlation between the current market, with the goal of minimizing CVaR function, established the optimal hedging ratio of static and dynamic measurement model based on the Copula-CVaR rate, and the model is studied. The Shanghai and Shenzhen 300 and the stock index futures as the research object, established the static and dynamic Copula-CVaR model and OLS model in a given period, set limits, analysis of the cost of insurance set of each model, and gives the correct cost of hedging efficiency is analyzed. The empirical results show that considering the hedging costs, should choose the static hedging strategy is simple and, even if the market conditions are the same, should also choose the optimal hedging strategy according to their own expenses.
This paper promotes the financial market risk measurement, futures hedging, the research of AL distribution and Copula function theory, is of great theoretical significance, at the same time on investment decisions, economic capital management and risk management practices also play a very good help and reference.

【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：F224;F831.51

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