Name
Title | ||
|---|---|---|
Forecasting Financial Time Series using Neural Network and Fuzzy System-based Techniques |
Abstract | ||
|---|---|---|
Forecasting currency exchange rates are an important financial problem that is receiving increasing attention, especially
because of its intrinsic difficulty and practical applications. During the last few years, a number of nonlinear models have
been proposed for obtaining accurate prediction results, in an attempt to ameliorate the performance of the traditional linear
approaches. Among them, neural network models have been used with encouraging results. This paper presents improved neural
network and fuzzy models used for exchange rate prediction. Several approaches, including multi-layer perceptions, radial
basis functions, dynamic neural networks and neuro-fuzzy systems, have been proposed and discussed. Their performances for
one-step and multiple step ahead predictions have been evaluated through a study, using real exchange daily rate values of
the US Dollar vs. British Pound. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/s005210200021 | Neural Computing and Applications |
Keywords | DocType | Volume |
neuro-fuzzy systems,forecasting,finance,neural networks,exchange rates | Journal | 11 |
Issue | ISSN | Citations |
2 | 1433-3058 | 47 |
PageRank | References | Authors |
2.54 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vassilis S. Kodogiannis | 1 | 272 | 35.17 |
| A. Lolis | 2 | 47 | 3.21 |