本文選題：VaR　切入點：非線性分位數(shù)回歸　出處：《天津科技大學》2013年碩士論文　論文類型：學位論文

【摘要】：在2001年加入WTO之后,我國的外匯儲備量已經(jīng)攀升到了世界第一的位置,而在2005年采用浮動匯率以來,人民幣匯率一直承受著外界政治、經(jīng)濟的多方壓力,導致人民幣匯率處于不斷增值的趨勢中,加之2008年金融危機對金融市場的巨大沖擊使得很多金融巨頭紛紛倒閉,金融行業(yè)得以重新洗牌,在新挑戰(zhàn)和新機遇并存的形勢下,加快我國金融行業(yè)監(jiān)管理論與實踐方面的水平變得尤其重要。目前,在經(jīng)過多年的研究與探索之后,基于VaR的金融市場風險度量方法業(yè)已成為國外諸多金融機構的重要風險控制工具。而國內(nèi)的匯率管理制度和匯率風險監(jiān)管方法仍然比較落后,不足以形成穩(wěn)定的匯率水平和先進的風險控制系統(tǒng)。在這種形勢下,對國際先進金融風險測度方法的學習與研究顯得尤為重要,本文在目前廣泛使用的VaR方法的基礎上進行了拓展與深入研究,主要從基于非線性分位數(shù)回歸的VaR估計方法角度展開。希望能夠為匯率風險監(jiān)管提供一種有力的工具。本文通過對人民幣/美元收益率序列進行統(tǒng)計分析發(fā)現(xiàn)該序列存在著非正態(tài)性、尖峰厚尾、非對稱性、波動集聚、條件方差性等特征。使用傳統(tǒng)的時間序列模型ARMA模型或者非線性最小二乘回歸模型對序列進行擬合,經(jīng)過檢驗發(fā)現(xiàn)這兩種模型不能刻畫該序列的這些特征。由于GARCH族模型充分利用了ARCH模型的條件異方差性和學生t分布和GED分布的尖峰厚尾的特性,經(jīng)過檢驗發(fā)現(xiàn)各種GARCH類模型均能很好的描述收益率序列的異方差性。經(jīng)過實證分析可以得出這樣的結論,非線性分位數(shù)回歸模型估計時序金融數(shù)據(jù)的VaR時,能夠全面刻畫金融數(shù)據(jù)之間不同相關結構下的相關關系從而能夠得出具有靈活性的度量方法和有多重選擇的結論。
[Abstract]:After joining the WTO in 2001, China's foreign exchange reserves have climbed to the first position in the world. Since 2005, when the floating exchange rate was adopted, the RMB exchange rate has been subject to external political and economic pressures. The RMB exchange rate is in the trend of increasing value. In addition, the huge impact of the financial crisis on the financial market in 2008 has caused many financial giants to close down one after another, and the financial industry has been able to reshuffle, under the situation of the coexistence of new challenges and new opportunities. It is particularly important to speed up the theoretical and practical level of financial industry supervision in China. At present, after many years of research and exploration, The financial market risk measurement method based on VaR has become an important risk control tool for many foreign financial institutions, while the domestic exchange rate management system and exchange rate risk supervision method are still relatively backward. It is not enough to form a stable exchange rate level and an advanced risk control system. In this situation, it is particularly important to study and study international advanced financial risk measurement methods. Based on the VaR method which is widely used at present, this paper has carried on the development and the thorough research. From the point of view of VaR estimation method based on nonlinear quantile regression, this paper hopes to provide a powerful tool for the supervision of exchange rate risk. The sequence is nonnormal, The characteristics of peak thick tail, asymmetry, fluctuation agglomeration, conditional variance, etc. The traditional time series model ARMA model or nonlinear least square regression model are used to fit the sequence. It is found that these two models can not describe these characteristics of the sequence. Because the GARCH family model makes full use of the conditional heteroscedasticity of the ARCH model and the characteristics of the student t distribution and the GED distribution, It is found that all kinds of GARCH models can describe the heteroscedasticity of the return series well. The conclusion can be drawn from the empirical analysis that the nonlinear quantile regression model can estimate the VaR of time series financial data. It can comprehensively describe the relationship between financial data under different correlation structures, so that we can get the flexible measurement method and the conclusion of multiple choices.
【學位授予單位】：天津科技大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F832.5;F224

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本文編號：1628399