Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Multi-disciplinary Studies | en_US |
| dc.contributor | Department of Applied Mathematics | en_US |
| dc.creator | Yip, Chi-kin | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/3140 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Time-series forecasting of foreign exchange rates using recurrent neural networks : a comparative study with statistical models | en_US |
| dcterms.abstract | Time series are a special form of data where past values in the series may influence future values, depending on the presence of underlying deterministic forces. Whilst linear models, such as those based on regression techniques, have been the basis of traditional statistical forecasting models, their drawbacks have led to increased activity in nonlinear modeling. Neural networks are nonlinear models that can be trained to map past and future values of time series, and thereby extract hidden structure and relationships governing the data. Economy is a dynamic system that inherits non-linearity through long term trends, seasonal patterns, cyclical movements, and irregular factors. This dissertation focus on the application of Recurrent Neural Networks (RNN) to predict Foreign Exchange (FX) time series. The RNN module performance is evaluated in terms of Direction matching, MAE, MAPE, and System stability using FX rate data set. This data set includes four currencies against United States Dollar (USD) as indicators that span over four years in daily price. The predictions are combined trading fuzzy decision making module to generate buy-sell-hold recommendations for the entire list of FX rates on a daily basis. Finally, a simple exponential smoothing (SES) model would be compared to RNN prediction. And the results are presented and concluded with a discussion on the ongoing research direction. | en_US |
| dcterms.extent | 97 leaves : ill. ; 30 cm + diskette | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 1998 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Foreign exchange rates -- Forecasting -- Mathematical models | en_US |
| dcterms.LCSH | Time series analysis | en_US |
| dcterms.LCSH | Neural networks (Computer science) | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b14285757.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.48 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/3140