本文關(guān)鍵詞： 外匯風(fēng)險(xiǎn) GARCH類模型 VAR方法 偏T分布　出處：《山東大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：自2005年7月21日中國實(shí)施匯率體制改革之后,人民幣匯率的變動(dòng)越來越頻繁；同時(shí),隨著中國加入WTO之后,在國際貨幣市場、資本市場所占有的份額也越來越大；中國已成為第一大外匯儲(chǔ)備國,但迫于國際政治勢力和經(jīng)濟(jì)因素,人民幣正面臨著升值的壓力,這樣一來對(duì)我國的外匯儲(chǔ)備將會(huì)在國際匯率市場上迅速貶值。在這樣的環(huán)境下,對(duì)外匯風(fēng)險(xiǎn)的管理就顯得尤為重要。 VAR方法是風(fēng)險(xiǎn)管理中主流風(fēng)險(xiǎn)度量方法,已被各國尤其是在西方發(fā)達(dá)國家的金融機(jī)構(gòu)和企業(yè)運(yùn)用。在中國,該方法大都運(yùn)用在相對(duì)比較成熟的股票市場,真正運(yùn)用在外匯市場的情況還不多。因此,本文嘗試著根據(jù)中國外匯市場收益率的統(tǒng)計(jì)特征,運(yùn)用基于各類GARCH類模型的VAR方法尋找一種適合我國具體情況的外匯風(fēng)險(xiǎn)度量方法。 本文通過對(duì)美元收益率R序列的特征分析發(fā)現(xiàn)序列存在著非正態(tài)性、尖峰厚尾、非對(duì)稱性、非獨(dú)立性、波動(dòng)集束、條件方差時(shí)變性以及長記憶性等特征。使用傳統(tǒng)的時(shí)間序列模型ARMA模型對(duì)序列擬合,經(jīng)過檢驗(yàn)ARMA模型不能處理序列的這些特征。由GARCH類模型的性質(zhì)利用GARCH類模型對(duì)R序列擬合,各種GARCH類模型均能很好的處理收益率序列的異方差效應(yīng)。為了綜合考慮各類模型對(duì)收益和損失的預(yù)測情況,分別計(jì)算高位95%、99%和低位5%、1%、0.5%以及0.25%基于各種GARCH類模型的VAR值,并進(jìn)行準(zhǔn)確性檢驗(yàn)：在低位隨著置信水平的增加,基于正態(tài)分布的各類GARCH模型都對(duì)VAR值高估(低估風(fēng)險(xiǎn))越來越嚴(yán)重,說明了相對(duì)于R序列正態(tài)分布的左側(cè)尾部太��；在高位95%、99%,基于T以及GED分布各類GARCH類模型的VAR值都出現(xiàn)了高估(高估收益),即相對(duì)于R序列分布的右側(cè)尾部較厚,但基于偏T分布的各類GARCH模型則基本都通過了檢驗(yàn),但對(duì)于下側(cè)VAR值,基于T分布的GARCH類模型對(duì)VAR值隨著置信水平的增加有一定的高估(低估風(fēng)險(xiǎn)),說明T分布的左側(cè)尾部相對(duì)于R序列稍��；GED分布的GARCH類模型對(duì)VAR值有一定的低估(高估風(fēng)險(xiǎn)),隨著置信水平的增加,高估程度越來越大,說明GED分布的左側(cè)尾部相對(duì)于R序列稍厚,說明R序列確實(shí)存在左偏的性質(zhì),左側(cè)尾部較厚,這也與近年了美元相比于人民幣呈現(xiàn)貶值的趨勢是一致的。但是基于偏態(tài)T分布的GARCH類模型對(duì)下側(cè)VAR值的預(yù)測隨著置信水平的增加,VAR值的低估(高估風(fēng)險(xiǎn))越來越嚴(yán)重；雖然偏T分布對(duì)于上側(cè)VAR值的預(yù)測與期望值較為接近,但在風(fēng)險(xiǎn)管理過程,風(fēng)險(xiǎn)比收益重要,所以在最優(yōu)模型的選擇上,還是以下側(cè)VAR值的預(yù)測結(jié)果為標(biāo)準(zhǔn),基于T分布和GED分布的各模型對(duì)于下側(cè)VAR值的預(yù)測較為穩(wěn)定,均值方程中帶有條件標(biāo)準(zhǔn)差模型優(yōu)于均值方程中不帶有條件標(biāo)準(zhǔn)差的模型,說明在外匯市場中收益是還是和風(fēng)險(xiǎn)緊密相連的,考慮對(duì)下側(cè)VAR值的預(yù)測值與期望值的接近程度,基于T分布的GARCH-M模型對(duì)VAR值的預(yù)測最接近期望值,且隨著置信水平的增加相對(duì)來說比較穩(wěn)定。 為了與GARCH類模型作比較,計(jì)算了基于ARMA模型的下側(cè)VAR值,并對(duì)其做準(zhǔn)確性檢驗(yàn)。從結(jié)果可以看出基于T分布的GARCH-M模型的對(duì)VAR值的估計(jì)的準(zhǔn)確性要遠(yuǎn)遠(yuǎn)優(yōu)于基于ARMA模型計(jì)算出的VAR值。
[Abstract]:After the implementation of the exchange rate system reform since July 21, 2005 China, changes in the RMB exchange rate is more and more frequent; at the same time, with the China after joining WTO, in the international monetary market, capital market share is growing; China has become the country's largest foreign exchange reserves, but under the international political and economic factors, the RMB appreciation is facing the pressure, as a result of China's foreign exchange reserves will depreciate rapidly in the international exchange market. Under such circumstances, the exchange risk management is particularly important.
The VAR method is the mainstream risk risk management measures, is in the world especially in the western developed countries, financial institutions and enterprises to use. In this method China, mostly used in relatively mature stock market, the real application in the foreign exchange market situation is not enough. Therefore, this paper try according to statistical characteristics of market returns Chinese the foreign exchange rate, using the VAR method of GARCH model based on finding a suitable to the situation of China's foreign exchange risk measurement method.
In this paper, through analyzing the characteristics of R sequence in the US yield found sequences exist non normality, leptokurtic, non symmetry, non independence, volatility cluster, time-varying conditional variance and long memory characteristic. Using the traditional time series ARMA model of sequence fitting, through the characteristic test of ARMA model can not handle the sequence. By the nature of the GARCH model with GARCH model to fit the R sequence, GARCH model can also heteroscedasticity effect processing good income rate series. In order to consider the various models of profit and loss forecast, calculate high of 95%, 99% and 5% lower, 1%. 0.5% and 0.25% kinds of GARCH model based on the VAR value, and the accuracy of the test: at a low level with the confidence level increases, the normal distribution of all kinds of GARCH models are based on the VAR value of overvalued (underestimate risk) is more and more serious, said Clear R sequences relative to normal distribution of the left tail is too thin; high in 95%, 99%, T and GED based on the distribution of all kinds of GARCH model VAR value appeared overvalued (overestimateearnings), namely R with respect to the right side of the rear sequence distribution is thick, but all kinds of partial GARCH model based on T distribution is basically through the test, but for the lower VAR value, the GARCH model of T distribution with the confidence level increases with some overestimation of VAR value based on T (underestimate risks), the distribution of the left tail relative to the R sequence of GARCH model is slightly thin; the distribution of GED have a low value of VAR (overestimate risk). With the increase of the confidence level, increasinglyovervalued. GED, the distribution of the left tail relative to the R sequence slightly thick, R series have left the nature of the left tail is thick, it is also associated with recent dollar compared to the RMB devaluation trend is presented The same. But the prediction model of GARCH skewed T distribution on the lower side based on the VAR value with the confidence level increases, the value of VAR (underestimate overestimate the risk is more and more serious); although the skewed T distribution for the prediction and expectation value is close to the VAR side, but in the process of risk management, risk return than important. So in the optimal model selection, or to predict the following side VAR value as the standard, T distribution and GED distribution of the model for predicting lower VAR value is more stable based on the mean equation with conditional standard deviation conditions standard deviation model with no model is better than the mean equation, illustrate the gains in the foreign exchange market is or risk closely linked, consider the forecast to the lower VAR value and expected value close to the degree, the GARCH-M model of T distribution prediction of VAR value of the expectations based on, and with the increase of relative confidence level It's more stable.
In order to compare with the GARCH class model, the lower side VAR value based on the ARMA model is calculated, and its accuracy is tested. From the result, we can see that the accuracy of the VAR estimation based on the T distribution model is much better than the VAR value calculated based on the ARMA model.

【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.6;F224

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