Forecasting Exchange Rates Using General Regression Neural Networks
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Forecasting Exchange Rates Using General Regression Neural Networks
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Author : Mark T. Leung
language : en
Publisher:
Release Date : 2004
Forecasting Exchange Rates Using General Regression Neural Networks written by Mark T. Leung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
In this study, we examine the forecastability of a specific neural network architecture called General Regression Neural Network (GRNN) and compare its performance with a variety of forecasting techniques, including Multi-Layered Feedforward Network (MLFN), multivariate transfer function, and random walk models. The comparison with MLFN provides a measure of GRNN's performance relative to the more conventional type of neural networks while the comparison with transfer function models examines the difference in predictive strength between the non-parametric and parametric techniques. The random walk model is used for benchmark comparison. Our findings show that GRNN not only has a higher degree of forecasting accuracy but also performs statistically better than other evaluated models for different currencies.
Forecasting Exchange Rates Using General Regression Neural Networks
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Author : Mark T. Leung
language : en
Publisher:
Release Date : 2006
Forecasting Exchange Rates Using General Regression Neural Networks written by Mark T. Leung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Predicting currency movements has always been a problematic task as most conventional econometric models are not able to forecast exchange rates with significantly higher accuracy than a naive random walk model. For large multinational firms which conduct substantial currency transfers in the course of business, being able to accurately forecast the movements of exchange rates can result in considerable improvement in the overall profitability of the firm. In this study, we apply the General Regression Neural Network (GRNN) to predict the monthly exchange rates of three currencies, British pound, Canadian dollar, and Japanese yen. Our empirical experiment shows that the performance of GRNN is better than other neural network and econometric techniques included in this study. The results demonstrate the predictive strength of GRNN and its potential for solving financial forecasting problems.
Foreign Exchange Rate Forecasting With Artificial Neural Networks
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Author : Lean Yu
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-02-26
Foreign Exchange Rate Forecasting With Artificial Neural Networks written by Lean Yu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-26 with Business & Economics categories.
This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting. The result is an up-to-date review of the most recent research developments in forecasting foreign exchange rates coupled with a highly useful methodological approach to predicting rate changes in foreign currency exchanges.
Regression Neural Network For Error Correction In Foreign Exchange Forecasting And Trading
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Author : An-Sing Chen
language : en
Publisher:
Release Date : 2006
Regression Neural Network For Error Correction In Foreign Exchange Forecasting And Trading written by An-Sing Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Predicting exchange rates has long been a concern in international finance as most standard econometric methods are unable to produce significantly better forecasts than the random walk model. Recent studies provide some evidence for the ability of using multivariate time series models to generate better forecasts. At the same time, artificial neural networks have been emerging as alternatives to predict exchange rates. In this paper, we propose an adaptive forecasting approach which combines the strengths of neural networks and multivariate econometric models. This hybrid approach contains two forecasting stages. In the first stage, a time series model generates estimates of the exchange rates. In the second stage, General Regression Neural Network is used to correct the errors of the estimates. A number of tests and statistical measures are then applied to compare the performances of the two-stage models (with error-correction by neural network) with those of the single-stage models (without error-correction by neural network). Both empirical and trading simulation experiments suggest that the proposed hybrid approach not only produces better exchange rate forecasts but also results in higher investment returns than the single-stage models. The effect of risk aversion in currency trading is also considered.
On Forecasting Exchange Rates Using Neural Networks
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Author : Philip Hans Franses
language : en
Publisher:
Release Date : 1996
On Forecasting Exchange Rates Using Neural Networks written by Philip Hans Franses and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with categories.
Performance Evaluation Of Neural Network Architectures
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Author : An-Sing Chen
language : en
Publisher:
Release Date : 2006
Performance Evaluation Of Neural Network Architectures written by An-Sing Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
In the last decade, neural networks have emerged from an esoteric instrument in academic research to a rather common tool assisting auditors, investors, portfolio managers and investment advisors in making critical financial decisions. A better understanding of the network's performance and limitations would help both researchers and practitioners in analysing real-world problems. This study evaluates and compares the performance of models based on two competing neural network architectures, the multi-layered feedforward neural network (MLFN) and general regression neural network (GRNN). Our empirical evaluation measures the network models' strength on the prediction of currency exchange correlation with respect to a variety of statistical tests including RMSE, MAE, U statistic, Theil's decomposition test, Henriksson-Merton market timing test and Fair-Shiller informational content test. Results of experiments suggest that the selection of proper architectural design may contribute directly to the success in neural network forecasting. In addition, market timing tests indicate that both MLFN and GRNN models have economically significant values in predicting the exchange rate correlation. On the other hand, informational content tests discover that the neural network models based on different architectures capture useful information not found in each other and the information sets captured by the two network designs are independent of one another. An auxiliary experiment is developed and confirms the possible synergetic effect from combining forecasts made by the two different network architectures and from incorporating information from an implied correlation model into the neural network forecasts.
Forecasting Foreign Exchange Rates Using Neural Networks
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Author : Amit H. Talati
language : en
Publisher:
Release Date : 2000
Forecasting Foreign Exchange Rates Using Neural Networks written by Amit H. Talati and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Foreign exchange rates categories.
Artificial Neural Networks On Foreign Exchange Rates
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Author : Adrian Luke Letchford
language : en
Publisher:
Release Date : 2010
Artificial Neural Networks On Foreign Exchange Rates written by Adrian Luke Letchford and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Neural computers categories.
"This thesis deals with three problems, mainly, whether or not data transformations enhance artificial neural network forecasting, as well as choosing the most appropriate loss functions and the ability of artificial neural networks to learn patterns in data. The data used is foreign exchange rates. It is impractical to guage loss functions with yet another loss function, thus, simple characteristics of the functions were isolated and examined for use in the given task. The results showed that while some functions are well suited to the problem of time series prediction, other can produce a less accurate fit subjective to the forecast problem. Previous work has shown time and time again that artificaial neural networks can produce superior results in comparison to other methods, however, an experiment was designed and conducted to determine if the neural networks were actually learning the patterns in the data rather that just producing a better fit. The results were mixed, showing that some exchange rates could beeasily learned while other could not. Finally, 20 different data transformations were compared to forecasting without preprocessing. The results found that 40% of the transformations improved the forecast. The basic and relative differencing functions, as well as one based on regression, were consistent across the time series used and were a statistically significant improvement." (ABSTRACT p. iv)
Forecasting Exchange Rates Using Feedforward And Recurrent Neural Networks
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Author : Chongming Guan
language : en
Publisher:
Release Date : 1994
Forecasting Exchange Rates Using Feedforward And Recurrent Neural Networks written by Chongming Guan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
Forecasting Exchange Rates Via Eemd Based Neural Networks
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Author : 余軒
language : en
Publisher:
Release Date : 2012
Forecasting Exchange Rates Via Eemd Based Neural Networks written by 余軒 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.