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  本文關(guān)鍵詞： 人民幣匯率 人民幣NDF報價 MRS-GARCH模型 最大似然估計法　出處：《東北財經(jīng)大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：30年來,我國匯率制度進(jìn)行了多次調(diào)整與改革,人民幣匯率也經(jīng)歷了多次復(fù)雜的變動。1994年,人民幣與美元非正式地掛鉤,但美元兌人民幣匯率只能在8.27至8.28元之間浮動。2005年,人民幣匯率以市場供求為基礎(chǔ)、參考一籃子貨幣進(jìn)行調(diào)節(jié)的、有管理的浮動匯率制度。2008年,美國次貸危機(jī)引發(fā)全球范圍的金融危機(jī),我國適當(dāng)調(diào)整人民幣波動幅度以應(yīng)對此次危機(jī)。2010年,中國銀行表示將進(jìn)一步推進(jìn)人民幣匯率形成機(jī)制改革。這些原因給人民幣匯率的波動狀況帶來不確定性,因此,對人民幣匯率行為的描述變得尤其困難。隨著近幾年國際上對人民幣升值壓力的不斷加大,對中國外匯市場的變動研究也顯得越來越重要。 本文在此研究背景下,以馬爾科夫狀態(tài)轉(zhuǎn)移模型與GARCH模型為理論基礎(chǔ),采用最大似然估計法,首先使用GARCH模型、EGARCH模型以及GJR模型對中國外匯市場波動情況進(jìn)行擬合估計,證實了其波動的非對稱性,即利空利好消息擁有的不同沖擊效應(yīng)。接著建立MRS-GARCH模型對中國外匯市場的波動情況進(jìn)行進(jìn)一步分析,將中國外匯市場的波動分為高波動狀態(tài)與低波動狀態(tài)兩個狀態(tài),通過馬爾科夫狀態(tài)轉(zhuǎn)移過程將兩個狀態(tài)的波動狀況進(jìn)行擬合,并從中得出了相關(guān)轉(zhuǎn)移概率及穩(wěn)態(tài)概率。在此分析過程中,針對序列表現(xiàn)出的偏峰厚尾分布,對各個模型采用不同的殘差項分布假定：正態(tài)分布、t分布、時變t分布以及廣義誤差分布。最后,根據(jù)AIC、BIC準(zhǔn)則以及損失函數(shù)的對比,對不同分布下的各個模型進(jìn)行比較,選出相對最優(yōu)模型進(jìn)行了進(jìn)一步分析。 本文在研究日度人民幣匯率收益率的前提下,又引入另一序列,即人民幣無本金交割遠(yuǎn)期合約報價收益率作為對比數(shù)據(jù),旨在加入市場行為的影響來進(jìn)行模型的比較,最終得到如下結(jié)論：①我國外匯市場的波動存在明顯的非線性特征；②我國外匯市場的波動具有非對稱性,即利好消息和利空消息對外匯市場等的沖擊大小并不相同；③我國外匯市場存在顯著的兩狀態(tài)轉(zhuǎn)移過程,處在兩狀態(tài)的轉(zhuǎn)移概率都較高,而且其各自的持續(xù)程度也較久；④人民幣NDF收益率考慮了市場行為的影響,因此與匯率收益率在波動情況下存在一定差異,但僅從GARCH族模型中看不到這種區(qū)別的顯著特征,而從最優(yōu)分布下的MRS-GARCH模型能夠?qū)⑦@種市場預(yù)測行為顯著的區(qū)別出來。 根據(jù)得出的實證結(jié)論,并結(jié)合我國外匯市場的實際特征,文章在最后以政府、金融機(jī)構(gòu)以及企業(yè)這三個角度出發(fā),對我國外匯市場體制改革、法律制度、衍生工具以及規(guī)避風(fēng)險等各個方面進(jìn)行了簡單分析及建議,從而建立一個更加成熟穩(wěn)定的外匯市場。
[Abstract]:Over the past 30 years, China's exchange rate regime has been adjusted and reformed many times, and the RMB exchange rate has undergone many complex changes. In 1994, the RMB was informally pegged to the US dollar, but the USD-to-RMB exchange rate could only fluctuate between 8.27 and 8.28 yuan. The RMB exchange rate is based on market supply and demand, with reference to a basket of currencies to regulate the managed floating exchange rate regime. In 2008, the US subprime mortgage crisis triggered a global financial crisis. On 2010, the Bank of China indicated that it would further promote the reform of the RMB exchange rate formation mechanism. These reasons have brought uncertainty to the volatility of the RMB exchange rate, so, It is particularly difficult to describe the behavior of the RMB exchange rate. With the increasing international pressure on the appreciation of the RMB in recent years, the study of the changes in China's foreign exchange market is becoming more and more important. In this background, based on Markov state transition model and GARCH model, the maximum likelihood estimation method is adopted. Firstly, the GARCH model and GJR model are used to estimate the volatility of China's foreign exchange market. The asymmetry of the volatility is confirmed, that is, the different impact effects of the good news. Then, the MRS-GARCH model is established to further analyze the volatility of China's foreign exchange market. The volatility of China's foreign exchange market is divided into two states: high volatility state and low volatility state. The volatility of the two states is fitted by Markov state transfer process. The correlation transfer probability and steady-state probability are obtained. In the process of this analysis, for the partial peak and thick tail distribution shown by the sequence, the different residual distribution assumption is adopted for each model: normal distribution / t distribution. The time-varying t distribution and generalized error distribution. Finally, according to the comparison of the AIC-BIC criterion and the loss function, the models under different distributions are compared, and the relative optimal model is selected for further analysis. On the premise of studying the daily rate of return of RMB exchange rate, this paper introduces another sequence, that is, the rate of return of RMB non-deliverable forward contract as the comparative data, in order to add the influence of market behavior to carry on the comparison of the model. Finally, we get the following conclusion: 1 the volatility of China's foreign exchange market has obvious nonlinear characteristics. Second, the volatility of China's foreign exchange market is asymmetric. That is, the impact of the good news and the bad news on the foreign exchange market is not the same. There is a significant two-state transfer process in our foreign exchange market, and the transfer probability of the two states is higher. Moreover, the NDF rate of return of RMB 4 has taken into account the influence of market behavior, so there is a certain difference between the rate of return and the rate of return in the case of fluctuation, but only from the GARCH family model there is no obvious characteristic of this difference. From the optimal distribution of the MRS-GARCH model can significantly distinguish this market forecast behavior. Based on the empirical conclusions and the actual characteristics of China's foreign exchange market, the article, at the end of the article, from the perspective of the government, financial institutions and enterprises, to the reform of the foreign exchange market system, the legal system, The derivatives and risk aversion are analyzed and suggested in order to establish a more mature and stable foreign exchange market.
【學(xué)位授予單位】：東北財經(jīng)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F224;F832.52

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