基于GARCH-Copula模型的國際原油價(jià)格與可再生能源股價(jià)相關(guān)性研究
發(fā)布時(shí)間：2018-10-23 15:00
【摘要】：進(jìn)入二十一世紀(jì)以來,隨著化石能源的日益枯竭以及人們對空氣環(huán)境質(zhì)量要求的日益提高,可再生能源走進(jìn)了人們的視野,并且在過去的十幾年里得到了快速的發(fā)展。根據(jù)國際能源署披露的數(shù)據(jù)表明,2014年全球可再生能源領(lǐng)域投資金額達(dá)2.7萬億美元。而可再生能源作為例如石油、煤炭等傳統(tǒng)能源的替代品,其發(fā)展或多或少的受到國際原油價(jià)格的影響。因此,就很有必要研究國際原油價(jià)格與可再生能源股價(jià)之間的相關(guān)關(guān)系,以幫助投資者更好的進(jìn)行可再生能源的投資決策。本文通過使用Copula函數(shù)描述國際原油價(jià)格與可再生能源股價(jià)之間的相關(guān)結(jié)構(gòu),建立了 GARCH-Copula模型。并且回顧了過往對國際原油價(jià)格、可再生能源及其二者相關(guān)性的研究,介紹了傳統(tǒng)相關(guān)性度量方法及其存在的一些缺點(diǎn),提出了使用Copula函數(shù)能夠更好的度量金融時(shí)間序列之間相關(guān)性的觀點(diǎn),比較詳細(xì)的介紹了 Copula函數(shù)的定義、性質(zhì)、分類以及與相關(guān)性度量方法的關(guān)系,最后提出引入Copula函數(shù)運(yùn)用蒙特卡洛模擬的方法計(jì)算投資組合VaR。本文選取2009年12月31日至2016年12月31日布倫特原油價(jià)格、Wind新能源指數(shù)、標(biāo)普全球清潔能源指數(shù)以及WilderHill清潔能源指數(shù)共1648組數(shù)據(jù)作為研究對象進(jìn)行實(shí)證研究。文章首先對四個(gè)收益率序列的邊緣分布進(jìn)行t-GARCH(1,1)建模,之后選取了正態(tài) Copula 函數(shù)、Gumbel Copula 函數(shù)、Clayton Copula函數(shù)以及Frank Copula函數(shù)對布倫特原油與三個(gè)可再生能源指數(shù)之間的相關(guān)結(jié)構(gòu)進(jìn)行建模,最后根據(jù)最優(yōu)Copula函數(shù)計(jì)算了尾部相關(guān)系數(shù)及投資組合的VaR,并且確定最優(yōu)投資組合。
[Abstract]:Since 21 century, with the increasing depletion of fossil energy and the increasing demand for air quality, renewable energy has come into people's vision, and has been rapidly developed in the past ten years. Investment in renewable energy globally reached $2.7 trillion in 2014, according to data released by the International Energy Agency. As a substitute for traditional energy such as oil and coal, the development of renewable energy is more or less affected by the international crude oil price. Therefore, it is necessary to study the correlation between the international crude oil price and the share price of renewable energy, so as to help investors make better investment decisions on renewable energy. In this paper, the GARCH-Copula model is established by using Copula function to describe the correlation structure between the international crude oil price and the share price of renewable energy. And reviewed the past research on the international crude oil price, renewable energy and their correlation, introduced the traditional correlation measurement methods and some shortcomings, This paper puts forward the viewpoint that using Copula function can better measure the correlation between financial time series, and introduces in detail the definition, property, classification of Copula function and the relationship between Copula function and correlation measurement method. Finally, the paper introduces Copula function to calculate portfolio VaR. by Monte Carlo simulation. From December 31, 2009 to December 31, 2016, Brent crude oil price, Wind new energy index, S & P global clean energy index and WilderHill clean energy index were selected for empirical research. In this paper, the edge distribution of four return sequences is first modeled by t-GARCH (1 / 1). Then the normal Copula function, Gumbel Copula function, Clayton Copula function and Frank Copula function are selected to model the correlation structure between Brent crude oil and three renewable energy indices. Finally, according to the optimal Copula function, the tail correlation coefficient and the VaR, of the portfolio are calculated and the optimal portfolio is determined.
【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F416.22;F831.51;F764.1
，
本文編號(hào)：2289591
[Abstract]:Since 21 century, with the increasing depletion of fossil energy and the increasing demand for air quality, renewable energy has come into people's vision, and has been rapidly developed in the past ten years. Investment in renewable energy globally reached $2.7 trillion in 2014, according to data released by the International Energy Agency. As a substitute for traditional energy such as oil and coal, the development of renewable energy is more or less affected by the international crude oil price. Therefore, it is necessary to study the correlation between the international crude oil price and the share price of renewable energy, so as to help investors make better investment decisions on renewable energy. In this paper, the GARCH-Copula model is established by using Copula function to describe the correlation structure between the international crude oil price and the share price of renewable energy. And reviewed the past research on the international crude oil price, renewable energy and their correlation, introduced the traditional correlation measurement methods and some shortcomings, This paper puts forward the viewpoint that using Copula function can better measure the correlation between financial time series, and introduces in detail the definition, property, classification of Copula function and the relationship between Copula function and correlation measurement method. Finally, the paper introduces Copula function to calculate portfolio VaR. by Monte Carlo simulation. From December 31, 2009 to December 31, 2016, Brent crude oil price, Wind new energy index, S & P global clean energy index and WilderHill clean energy index were selected for empirical research. In this paper, the edge distribution of four return sequences is first modeled by t-GARCH (1 / 1). Then the normal Copula function, Gumbel Copula function, Clayton Copula function and Frank Copula function are selected to model the correlation structure between Brent crude oil and three renewable energy indices. Finally, according to the optimal Copula function, the tail correlation coefficient and the VaR, of the portfolio are calculated and the optimal portfolio is determined.
【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F416.22;F831.51;F764.1
，
本文編號(hào)：2289591
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