【摘要】：任何金融產(chǎn)品投資都有風(fēng)險(xiǎn),匯率也同樣帶有風(fēng)險(xiǎn),但它是把雙刃劍,由于內(nèi)在的不確定性,使得匯率風(fēng)險(xiǎn)不僅能夠給企業(yè)帶來一定的損失,同樣還有可能帶來收益。越來越多的散戶投資者及企業(yè)開始進(jìn)入外匯市場,在充分了解外匯市場匯率波動(dòng)情況后,利用一定規(guī)律來獲得利潤,特別是對于一些出口企業(yè)而言,他們可以重視外匯風(fēng)險(xiǎn)的估計(jì)和度量,以此來降低風(fēng)險(xiǎn),提高抵抗風(fēng)險(xiǎn)的能力。同時(shí),要與相關(guān)部門緊密聯(lián)系,例如政府財(cái)政部門、銀行、保險(xiǎn)公司等,獲得更多的信息,加強(qiáng)風(fēng)險(xiǎn)預(yù)警。在對金融資產(chǎn)投資組合進(jìn)行分析時(shí),相關(guān)性研究及其使用一種有效的聯(lián)合分布模型十分重要,但是,傳統(tǒng)的相關(guān)性分析,系數(shù)確定方面帶有很大的局限性。因此,要充分了解和研究相關(guān)性分析中的每一個(gè)環(huán)節(jié),例如投資組合、風(fēng)險(xiǎn)管理、資產(chǎn)定價(jià)、波動(dòng)傳導(dǎo)及溢出等多種變量,爭取做到恰當(dāng)更精準(zhǔn)地分析金融資產(chǎn)風(fēng)險(xiǎn)問題。 風(fēng)險(xiǎn)度量方面,VaR已成為應(yīng)用最為廣泛的方法,也是金融風(fēng)險(xiǎn)研究的重點(diǎn)；通過Copula構(gòu)建金融資產(chǎn)組合的聯(lián)合分布函數(shù)創(chuàng)造了一條便捷、科學(xué)的方法,使該聯(lián)合分布可以滿足金融資產(chǎn)所固有的尖峰厚尾特性——非正態(tài)、非線性相關(guān),可以解決傳統(tǒng)風(fēng)險(xiǎn)管理模型的正態(tài)線性相關(guān)性假設(shè)。 本文研究內(nèi)容主要是多種金融資產(chǎn)投資組合的相關(guān)性分析、度量問題,通過實(shí)例來研究Copula理論的建模方法及應(yīng)用�；贑opula理論,通過將Copula函數(shù).GARCH模型、VaR以及Monte Carlo方法有機(jī)結(jié)合,解決了多種金融資產(chǎn)的非正態(tài)、非線性相關(guān)建模問題,并且通過使用嵌套阿基米德Copula建立高維資產(chǎn)組合模型。首先第一部分實(shí)證研究對象是中國外匯市場幾種主要外匯資產(chǎn)的投資組合,先通過GARCH模型族的比較研究確定了單個(gè)風(fēng)險(xiǎn)資產(chǎn)收益率的邊際分布波動(dòng)模型；然后運(yùn)用PC算法估計(jì)了表示資產(chǎn)間相關(guān)結(jié)構(gòu),基于嵌套阿基米德Copula建模思想構(gòu)建了高維嵌套阿基米德Copula模型,該模型能更好的描述資產(chǎn)組合間的相依結(jié)構(gòu)；在高維嵌套阿基米德Copula模型的基礎(chǔ)上利用Monte Carlo方法模擬了資產(chǎn)組合的VaR,并通過返回檢驗(yàn)證明了模型的有效性。其次第二部分的實(shí)證研究是以中國外匯市場上四種外匯資產(chǎn)組合為對象,在該部分的研究中采用基于Pair Copula高維建模方法的混合C藤Copula模型及D藤Copula模型比較研究,實(shí)證外匯資產(chǎn)投資組合VaR的研究。在實(shí)證研究中,將兩類模型在資產(chǎn)組合VaR計(jì)算精度方面進(jìn)行比較。兩部分的實(shí)證研究結(jié)果都表明,所建立的Copula模型都能更好的刻畫金融資產(chǎn)間的相關(guān)結(jié)構(gòu),為風(fēng)險(xiǎn)度量方面提供便利條件。
[Abstract]:Any investment in financial products has risks, and exchange rate also has risks, but it is a double-edged sword. Because of the inherent uncertainty, exchange rate risk can not only bring certain losses to enterprises, but also may bring benefits. More and more retail investors and enterprises begin to enter the foreign exchange market. After fully understanding the exchange rate fluctuations in the foreign exchange market, they make use of certain rules to make profits, especially for some export enterprises. They can value the estimation and measurement of foreign exchange risk to reduce risk and improve their ability to resist it. At the same time, close contact with relevant departments, such as government finance departments, banks, insurance companies and so on, to obtain more information, strengthen risk warning. In the analysis of financial asset portfolio, it is very important to study the correlation and use an effective joint distribution model. However, the traditional correlation analysis and coefficient determination have great limitations. Therefore, we should fully understand and study every link in the correlation analysis, such as portfolio, risk management, asset pricing, volatility conduction and spillover, in order to analyze financial asset risk properly and accurately. In the aspect of risk measurement, VaR has become the most widely used method, and it is also the focus of financial risk research, which creates a convenient and scientific method to construct the joint distribution function of financial portfolio through Copula. The joint distribution can satisfy the characteristics of the financial assets such as non-normal, nonlinear correlation, and can solve the normal linear correlation hypothesis of the traditional risk management model. This paper mainly focuses on the correlation analysis and measurement of the portfolio of various financial assets, and studies the modeling method and application of Copula theory through examples. Based on Copula theory, by combining Copula function. GARCH model with Monte Carlo method, this paper solves the problem of non-normal and nonlinear correlation modeling of various financial assets, and establishes a high-dimensional portfolio model by using nested Archimedes Copula. The first part of the empirical research object is the portfolio of several major foreign exchange assets in China's foreign exchange market. Firstly, through the comparative study of GARCH model family, the marginal distribution volatility model of the return rate of individual risk assets is determined. Then using PC algorithm to estimate the correlation structure between assets, based on nested Archimedes Copula modeling idea to construct a high-dimensional nested Archimedean Copula model, this model can better describe the dependent structure between asset combinations; Based on the high dimensional nested Archimedes Copula model, the Monte Carlo method is used to simulate the VaR, of the portfolio and the validity of the model is proved by the return test. The second part of the empirical research is based on the Chinese foreign exchange market four foreign exchange portfolio as the object, in this part of the study based on Pair Copula high-dimensional modeling method based on mixed C-rattan Copula model and D-rattan Copula model comparative study. Empirical study of foreign exchange portfolio VaR. In the empirical study, the two models are compared in the accuracy of portfolio VaR calculation. The results of the two parts of empirical research show that the established Copula model can better describe the correlation structure between financial assets and provide convenient conditions for risk measurement.
【學(xué)位授予單位】：天津科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F830;F224

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