基于NDF与NARX网络的人民币汇率预测研究
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摘要
在经济高度全球化的今天,汇率在国际经济中的地位越来越重要,越来越深刻的影响着各国之间的经济与贸易往来。本文研究的目的就是为汇率预测寻求一种新的方法,以此规避汇率变动所带来的风险,这对国家和涉外经济体都有着十分重要的意义。
在对汇率的决定理论,可能影响汇率的因素,以及汇率预测的方法等进行研究和探索时,我们发现无本金交割远期外汇(Non Deliverable Forwards,简称NDF)这种金融衍生物与汇率之间存在着很大的联系,所以我们试图寻找一种新的,不同于以往理论模型和线性预测方法的非线性预测方法,加入NDF这种经济变量,以提高预测的精度,并对国家和涉外企业等提供良好的规避汇率风险的理论和方法。
本文选用有外部输入的非线性自回归神经网络(Nonlinear Auto Regressive Neural Network with Exogenous Inputs),简称NARX网络,建立NARX人民币汇率预测网络,由于NDF在一定程度上可以代表政策出台时市场的反应,所以它可以作为NARX网络的外部输入,以改善在突发政策时,NARX网络在汇率预测方面的性能。在无政策出台时,使用NDF作为外部输入和不使用NDF的预测结果基本一致,NDF值与汇率变动值存在较明显的相关性。在出台政策的较短时间内,有NDF加入网络的性能优于无NDF加入的网络。长时间来看,预测人民币汇率时,引入NDF的NARX网络的误差小于无NDF的NAR网络,所以引入NDF的NARX网络用于汇率预测是有效的可行方案。选取人民币两次汇改前后数据对人民币汇率进行了预测,取得了良好的效果。
在确定了NDF在汇率预测中的有效性之后,我们尝试找出究竟哪种NDF用于人民币汇率预测时的效果最好。从数据实验结果发现,NDF期限越短,与即期市场的互动关系越强,而常被以往文献用来研究与即期市场关联性的1年期NDF,其并不是与即期市场互动关系最强的。NDF合约的交易量、流动性对其与即期市场的互动关系有一定的影响,但不是决定性的。五个不同合约期限的NDF数据用于汇率预测的效果都很好,进一步验证了NDF在汇率预测中的有效性。
本文衡量了汇改后人民币汇率市场化进程,试图从定性和定量两个角度来衡量人民币市场化进程。我们将韩币NDF作为外部输入加入到前文所建立的NARX网络中,发现韩币NDF可以很好地对人民币汇率走势进行预测,预测效果良好。说明人民币汇率走势已同国际外汇市场有效接轨,并且可以再一次验证,人民币汇率市场化进展顺利。
With the great econimic globalization today, the position of excange rate has come to a high degree in international economic. It is the bridge that connects each country. The purpose of this study is to seek a new way of exchange rate forecasting, in order to avoid the risks from changes of exchange rate, which have a great significance to both national and foreign-ralated enterprises.
During our study of research and explorations about decision theorys of exchange rate, factors that may affect exchange rate. and methods used for exchange rate forecasting, Non Deliverable Forwards, which is known as NDF for short, comes into our view of research. NDF is a kind of forward exchange transactions, is a kind of derivative financial instruments. We found that there is a strong connection between the NDF derivatives and exchange rate, and in this case we try to find a new nonlinear method for forecasting different from the previous theoretical models and linear forecasting methods. Add NDF this kind of economic variables, in order to improve the accuracy of forecasting, and provide theory and method to avoid exchange rate risk for national and foreign-related enterprises.
In this paper we selected Nonlinear Auto Regressive neural network with exogenous inputs, NARX network for short, and established a network to forecast RMB exchange rate.Because of its quick reaction of the market when policies published to a certain extent, NDF can be used as the external input of NARX network to improve the performance of exchange rate forecasting network when emergency policies anouced.
Using or using not NDF as an external input does not have a great influnce to the result of forecasting when no policies published, and NDF values are correlated with changes in the exchange rate significantly. In a relatively short period after policies published, forecasting network with NDF has advatages to network without NDF. In long term, the error of NARX forecasting network is less than NAR network without NDF as a external input.In this case, the introduction of NDF into NARX network for exchange rate forecasting is effectively feasible. In this paper, we select exchange rate data before and after the reform of RMB exchange rate to do the forecasting and achieved good results.
After the effectiveness of the NDF in the forecasting of exchange rate is determined, we try to find out what type of NDF is the most suitable one for RMB exchange rate forecasting. From the experimental results,1-year NDF which is often seleced to research the correlation between NDF and spot market because of its largest trading volume and highest liquidity is not the one that has the strongest interaction relationship with spot market. Trading volume and liquidity of the NDF market have a certain effect on the interactive relationship with spot market, but not decisive. Five different kind of NDF with different period of contract are all have good result when using in exchange rate forecasting, and further verify the effectiveness of the NDF in exchange rate forecasting.
This paper measures the process of RMB exchange rate market-oriented in seven years after reform, and trying to seek a quantitative method to illustrate the process of RMB marketization. We use Krean Won NDF as external input of the previously established NARX network, and found that Krean Won NDF can fit the trend of RMB exchange rate well in forecasting, the effect of forecasting is good. We get a further verification that the process of RMB exchange rate marketization is gradually and smoothly.
在对汇率的决定理论,可能影响汇率的因素,以及汇率预测的方法等进行研究和探索时,我们发现无本金交割远期外汇(Non Deliverable Forwards,简称NDF)这种金融衍生物与汇率之间存在着很大的联系,所以我们试图寻找一种新的,不同于以往理论模型和线性预测方法的非线性预测方法,加入NDF这种经济变量,以提高预测的精度,并对国家和涉外企业等提供良好的规避汇率风险的理论和方法。
本文选用有外部输入的非线性自回归神经网络(Nonlinear Auto Regressive Neural Network with Exogenous Inputs),简称NARX网络,建立NARX人民币汇率预测网络,由于NDF在一定程度上可以代表政策出台时市场的反应,所以它可以作为NARX网络的外部输入,以改善在突发政策时,NARX网络在汇率预测方面的性能。在无政策出台时,使用NDF作为外部输入和不使用NDF的预测结果基本一致,NDF值与汇率变动值存在较明显的相关性。在出台政策的较短时间内,有NDF加入网络的性能优于无NDF加入的网络。长时间来看,预测人民币汇率时,引入NDF的NARX网络的误差小于无NDF的NAR网络,所以引入NDF的NARX网络用于汇率预测是有效的可行方案。选取人民币两次汇改前后数据对人民币汇率进行了预测,取得了良好的效果。
在确定了NDF在汇率预测中的有效性之后,我们尝试找出究竟哪种NDF用于人民币汇率预测时的效果最好。从数据实验结果发现,NDF期限越短,与即期市场的互动关系越强,而常被以往文献用来研究与即期市场关联性的1年期NDF,其并不是与即期市场互动关系最强的。NDF合约的交易量、流动性对其与即期市场的互动关系有一定的影响,但不是决定性的。五个不同合约期限的NDF数据用于汇率预测的效果都很好,进一步验证了NDF在汇率预测中的有效性。
本文衡量了汇改后人民币汇率市场化进程,试图从定性和定量两个角度来衡量人民币市场化进程。我们将韩币NDF作为外部输入加入到前文所建立的NARX网络中,发现韩币NDF可以很好地对人民币汇率走势进行预测,预测效果良好。说明人民币汇率走势已同国际外汇市场有效接轨,并且可以再一次验证,人民币汇率市场化进展顺利。
With the great econimic globalization today, the position of excange rate has come to a high degree in international economic. It is the bridge that connects each country. The purpose of this study is to seek a new way of exchange rate forecasting, in order to avoid the risks from changes of exchange rate, which have a great significance to both national and foreign-ralated enterprises.
During our study of research and explorations about decision theorys of exchange rate, factors that may affect exchange rate. and methods used for exchange rate forecasting, Non Deliverable Forwards, which is known as NDF for short, comes into our view of research. NDF is a kind of forward exchange transactions, is a kind of derivative financial instruments. We found that there is a strong connection between the NDF derivatives and exchange rate, and in this case we try to find a new nonlinear method for forecasting different from the previous theoretical models and linear forecasting methods. Add NDF this kind of economic variables, in order to improve the accuracy of forecasting, and provide theory and method to avoid exchange rate risk for national and foreign-related enterprises.
In this paper we selected Nonlinear Auto Regressive neural network with exogenous inputs, NARX network for short, and established a network to forecast RMB exchange rate.Because of its quick reaction of the market when policies published to a certain extent, NDF can be used as the external input of NARX network to improve the performance of exchange rate forecasting network when emergency policies anouced.
Using or using not NDF as an external input does not have a great influnce to the result of forecasting when no policies published, and NDF values are correlated with changes in the exchange rate significantly. In a relatively short period after policies published, forecasting network with NDF has advatages to network without NDF. In long term, the error of NARX forecasting network is less than NAR network without NDF as a external input.In this case, the introduction of NDF into NARX network for exchange rate forecasting is effectively feasible. In this paper, we select exchange rate data before and after the reform of RMB exchange rate to do the forecasting and achieved good results.
After the effectiveness of the NDF in the forecasting of exchange rate is determined, we try to find out what type of NDF is the most suitable one for RMB exchange rate forecasting. From the experimental results,1-year NDF which is often seleced to research the correlation between NDF and spot market because of its largest trading volume and highest liquidity is not the one that has the strongest interaction relationship with spot market. Trading volume and liquidity of the NDF market have a certain effect on the interactive relationship with spot market, but not decisive. Five different kind of NDF with different period of contract are all have good result when using in exchange rate forecasting, and further verify the effectiveness of the NDF in exchange rate forecasting.
This paper measures the process of RMB exchange rate market-oriented in seven years after reform, and trying to seek a quantitative method to illustrate the process of RMB marketization. We use Krean Won NDF as external input of the previously established NARX network, and found that Krean Won NDF can fit the trend of RMB exchange rate well in forecasting, the effect of forecasting is good. We get a further verification that the process of RMB exchange rate marketization is gradually and smoothly.
引文
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