本文選題：原油 + 價格風(fēng)險��； 參考：《華僑大學(xué)》2012年碩士論文

【摘要】：本文從原油的金融屬性、油價風(fēng)險的產(chǎn)生和控制，以及風(fēng)險的定量分析等方面入手，對中國原油價格風(fēng)險進行了研究。在我國的各大油田之中，大慶油田是產(chǎn)油量最大的，國際上也將大慶原油價格作為中國原油價格的代表，因此本文選取大慶原油價格作為中國原油價格的代表進行實證研究，從而為我國的原油價格風(fēng)險管理提供一定的參考作用。 在險價值（VaR）是當今風(fēng)險量化的主要方法，是應(yīng)用最為廣泛的風(fēng)險度量工具。該方法具有簡潔、明了的特點。但是，傳統(tǒng)的VaR計算方法一般都要對金融收益序列的分布做出假設(shè)，某種程度上降低了模型的可信度，而且廣泛采用的正態(tài)分布假設(shè)也不能完全反映實際金融收益的尖峰厚尾特征。作為關(guān)注風(fēng)險管理的人，他們最需要得到的信息又恰恰是關(guān)于較高分位數(shù)的尾部。因此，本文利用GARCH模型對于大慶原油收益率序列建模，描述其隨時間的波動性；選用極值理論中的POT模型對于標準殘差序列建模，描述其尾部特征。兩者結(jié)合起來可以計算出原油收益率序列的VaR值。 通過后驗測試與其它傳統(tǒng)度量VaR的模型比對，得出以下結(jié)論：第一，GARCH-EVT模型在95%置信水平下與GARCH-normal出錯率一致，并且小于GARCH-t模型和GARCH-GED模型；第二，，97.5%和99%置信水平下，GARCH-EVT模型出錯率小于GARCH-normal模型、 GARCH-t模型和GARCH-GED模型，顯示出在極端事件發(fā)生時的優(yōu)勢；第三，盡管落后于GARCH-EVT模型，但GARCH-GED模型在97.5%和99%置信水平下出錯率小于GARCH-normal模型和GARCH-t模型。最后進行了Kupiec似然比率檢驗，結(jié)果顯示了模型的有效性和準確性�？傮w說來，GARCH-EVT模型在度量中國原油價格風(fēng)險時更精確，出錯率更小，更適合作為中國原油市場的風(fēng)險管理的工具。
[Abstract]:In this paper, the financial property of crude oil, the production and control of oil price risk, and the quantitative analysis of oil price risk are studied in this paper. Among the major oil fields in China, Daqing oil field is the largest oil production, and the international Daqing crude oil price is also regarded as the representative of China crude oil price. Therefore, this paper selects Daqing crude oil price as the representative of China crude oil price to carry on the empirical research. So as to provide a certain reference for China's crude oil price risk management. Value-at-risk (VaR) is the main method of risk quantification and the most widely used risk measurement tool. The method is simple and clear. However, the traditional VaR calculation methods generally assume the distribution of the financial return series, which reduces the credibility of the model to some extent. Moreover, the widely used hypothesis of normal distribution can not completely reflect the peak and thick tail characteristics of actual financial returns. As people who care about risk management, what they need most is the end of the higher quartile. Therefore, the GARCH model is used to model Daqing crude oil yield series, which describes the volatility with time, and the POT model in extreme value theory is used to model the standard residual series to describe the tail characteristics. Combined, the VaR value of crude oil yield series can be calculated. By comparing the posteriori test with other traditional VaR models, the following conclusions are drawn: first, the GARCH-EVT model is consistent with the GARCH-normal error rate at 95% confidence level and is smaller than the GARCH-t model and GARCH-GED model; The error rate of GARCH-EVT model is lower than that of GARCH-normal model, GARCH-t model and GARCH-GED model at the second, 97.5% and 99% confidence levels. Third, although it lags behind the GARCH-EVT model, the GARCH-EVT model shows its advantages in the event of extreme events. But the error rate of GARCH-GED model is smaller than that of GARCH-normal model and GARCH-t model at 97.5% and 99% confidence level. Finally, the Kupiec likelihood ratio test is carried out, and the results show the validity and accuracy of the model. Generally speaking, GARCH-EVT model is more accurate and less error rate in measuring the risk of Chinese crude oil price, so it is more suitable as a tool for risk management in Chinese crude oil market.
【學(xué)位授予單位】：華僑大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：F426.22;F764.1;F832

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