本文選題：人民幣匯率 + 預測��； 參考：《大連理工大學》2013年博士論文

【摘要】：在經(jīng)濟高度全球化的今天,匯率在國際經(jīng)濟中的地位越來越重要,越來越深刻的影響著各國之間的經(jīng)濟與貿易往來。本文研究的目的就是為匯率預測尋求一種新的方法,以此規(guī)避匯率變動所帶來的風險,這對國家和涉外經(jīng)濟體都有著十分重要的意義。 在對匯率的決定理論,可能影響匯率的因素,以及匯率預測的方法等進行研究和探索時,我們發(fā)現(xiàn)無本金交割遠期外匯(Non Deliverable Forwards,簡稱NDF)這種金融衍生物與匯率之間存在著很大的聯(lián)系,所以我們試圖尋找一種新的,不同于以往理論模型和線性預測方法的非線性預測方法,加入NDF這種經(jīng)濟變量,以提高預測的精度,并對國家和涉外企業(yè)等提供良好的規(guī)避匯率風險的理論和方法。 本文選用有外部輸入的非線性自回歸神經(jīng)網(wǎng)絡(Nonlinear Auto Regressive Neural Network with Exogenous Inputs),簡稱NARX網(wǎng)絡,建立NARX人民幣匯率預測網(wǎng)絡,由于NDF在一定程度上可以代表政策出臺時市場的反應,所以它可以作為NARX網(wǎng)絡的外部輸入,以改善在突發(fā)政策時,NARX網(wǎng)絡在匯率預測方面的性能。在無政策出臺時,使用NDF作為外部輸入和不使用NDF的預測結果基本一致,NDF值與匯率變動值存在較明顯的相關性。在出臺政策的較短時間內,有NDF加入網(wǎng)絡的性能優(yōu)于無NDF加入的網(wǎng)絡。長時間來看,預測人民幣匯率時,引入NDF的NARX網(wǎng)絡的誤差小于無NDF的NAR網(wǎng)絡,所以引入NDF的NARX網(wǎng)絡用于匯率預測是有效的可行方案。選取人民幣兩次匯改前后數(shù)據(jù)對人民幣匯率進行了預測,取得了良好的效果。 在確定了NDF在匯率預測中的有效性之后,我們嘗試找出究竟哪種NDF用于人民幣匯率預測時的效果最好。從數(shù)據(jù)實驗結果發(fā)現(xiàn),NDF期限越短,與即期市場的互動關系越強,而常被以往文獻用來研究與即期市場關聯(lián)性的1年期NDF,其并不是與即期市場互動關系最強的。NDF合約的交易量、流動性對其與即期市場的互動關系有一定的影響,但不是決定性的。五個不同合約期限的NDF數(shù)據(jù)用于匯率預測的效果都很好,進一步驗證了NDF在匯率預測中的有效性。 本文衡量了匯改后人民幣匯率市場化進程,試圖從定性和定量兩個角度來衡量人民幣市場化進程。我們將韓幣NDF作為外部輸入加入到前文所建立的NARX網(wǎng)絡中,發(fā)現(xiàn)韓幣NDF可以很好地對人民幣匯率走勢進行預測,預測效果良好。說明人民幣匯率走勢已同國際外匯市場有效接軌,并且可以再一次驗證,人民幣匯率市場化進展順利。
[Abstract]:In today's highly globalized economy, the exchange rate plays a more and more important role in the international economy and has a profound impact on the economic and trade exchanges between countries. The purpose of this study is to find a new method to avoid the risk of exchange rate change, which is of great significance to both countries and foreign economies. In the course of studying and exploring the theory of exchange rate determination, the factors that may affect exchange rate, and the methods of exchange rate prediction, We found that there was a strong link between the non-deliverable forwards (NDF), a financial derivative, and the exchange rate, so we tried to find a new one. Different from the previous theoretical models and linear forecasting methods, NDF is added as an economic variable to improve the accuracy of prediction, and to provide a good theory and method to avoid exchange rate risk for countries and foreign enterprises. In this paper, nonlinear Auto recurrent neural network with inputs (NARX network) is used to establish the NARX RMB exchange rate forecasting network. To some extent, NDF can represent the market reaction when the policy is introduced. So it can be used as the external input of NARX network to improve the performance of NARX network in exchange rate prediction in case of sudden policy. In the absence of policy, the results of using NDF as external input and not using NDF are basically consistent. There is a significant correlation between NDF and exchange rate change. In a short period of time, the performance of NDF joining the network is better than that of the network without NDF. In a long time, the error of NARX network with NDF is less than that of NAR network without NDF, so it is feasible to use NARX network of NDF to predict exchange rate. The data before and after the two RMB exchange rate reforms are selected to predict the RMB exchange rate, and good results have been obtained. After determining the effectiveness of NDF in exchange rate forecasting, we try to find out which NDF is the most effective in RMB exchange rate forecasting. It is found from the data experiment that the shorter the NDF period, the stronger the interaction with spot market. However, the one-year NDFs, which are often used to study the relationship between NDF and spot market, are not the trading volume of .NDF contract, which has the strongest interaction with spot market. Liquidity has a certain influence on the interaction with spot market, but it is not decisive. Five NDF data with different contract duration have good effect on exchange rate forecasting, which further verifies the effectiveness of NDF in exchange rate forecasting. This paper measures the marketization process of RMB exchange rate after the exchange rate reform, and tries to measure the marketization process of RMB from two aspects: qualitative and quantitative. We add Korean NDF as external input to the NARX network, and find that Korean NDF can predict the trend of RMB exchange rate very well, and the forecast effect is good. It shows that the trend of RMB exchange rate has been effectively connected with the international foreign exchange market, and it can be verified once again that the marketization of RMB exchange rate is progressing smoothly.
【學位授予單位】：大連理工大學
【學位級別】：博士
【學位授予年份】：2013
【分類號】：F832.6;F224

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