Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural Networks
This paper proposes application of sliding window technique to time-delay neural network (TDNN) for prediction of financial time series. Neural network is a data-driven approach, in which we have huge data samples but limited information about the model structure. In this paper, we measure performan...
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| Format: | Article |
| Language: | fas |
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Allameh Tabataba'i University Press
2015-06-01
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| Series: | Faslnāmah-i Pizhūhish/Nāmah-i Iqtisādī |
| Subjects: | |
| Online Access: | https://joer.atu.ac.ir/article_1648_de0a3c717335fe6d0cbb72cc915e3947.pdf |
| _version_ | 1797375690895523840 |
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| author | Mohammadreza Asghari Oskoei |
| author_facet | Mohammadreza Asghari Oskoei |
| author_sort | Mohammadreza Asghari Oskoei |
| collection | DOAJ |
| description | This paper proposes application of sliding window technique to time-delay neural network (TDNN) for prediction of financial time series. Neural network is a data-driven approach, in which we have huge data samples but limited information about the model structure. In this paper, we measure performance of the prediction and apply sliding window technique to select the most favorable neural network structure, time-delay taps and the most desirable training data size that result in the best prediction performance. The method was evaluated by using real data of share price of four firms traded in London Stock Exchange. The results show remarkable decrease for the root mean squared error, mean absolute percentage error and the linear regression of TDNN output offset. |
| first_indexed | 2024-03-08T19:28:05Z |
| format | Article |
| id | doaj.art-fa1a54da225b4657864c32965166e6ae |
| institution | Directory Open Access Journal |
| issn | 1735-210X 2476-6453 |
| language | fas |
| last_indexed | 2024-03-08T19:28:05Z |
| publishDate | 2015-06-01 |
| publisher | Allameh Tabataba'i University Press |
| record_format | Article |
| series | Faslnāmah-i Pizhūhish/Nāmah-i Iqtisādī |
| spelling | doaj.art-fa1a54da225b4657864c32965166e6ae2023-12-26T08:00:30ZfasAllameh Tabataba'i University PressFaslnāmah-i Pizhūhish/Nāmah-i Iqtisādī1735-210X2476-64532015-06-011557751081648Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural NetworksMohammadreza Asghari Oskoei0Assistant Professor, Department of Mathematics and Computer Science, Allameh Tabataba’i UniversityThis paper proposes application of sliding window technique to time-delay neural network (TDNN) for prediction of financial time series. Neural network is a data-driven approach, in which we have huge data samples but limited information about the model structure. In this paper, we measure performance of the prediction and apply sliding window technique to select the most favorable neural network structure, time-delay taps and the most desirable training data size that result in the best prediction performance. The method was evaluated by using real data of share price of four firms traded in London Stock Exchange. The results show remarkable decrease for the root mean squared error, mean absolute percentage error and the linear regression of TDNN output offset.https://joer.atu.ac.ir/article_1648_de0a3c717335fe6d0cbb72cc915e3947.pdftime series predictiontime-delay neural networkssliding windowprediction errors |
| spellingShingle | Mohammadreza Asghari Oskoei Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural Networks Faslnāmah-i Pizhūhish/Nāmah-i Iqtisādī time series prediction time-delay neural networks sliding window prediction errors |
| title | Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural Networks |
| title_full | Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural Networks |
| title_fullStr | Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural Networks |
| title_full_unstemmed | Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural Networks |
| title_short | Application of Sliding Window for Financial Time Series Prediction using Time-Delay Neural Networks |
| title_sort | application of sliding window for financial time series prediction using time delay neural networks |
| topic | time series prediction time-delay neural networks sliding window prediction errors |
| url | https://joer.atu.ac.ir/article_1648_de0a3c717335fe6d0cbb72cc915e3947.pdf |
| work_keys_str_mv | AT mohammadrezaasgharioskoei applicationofslidingwindowforfinancialtimeseriespredictionusingtimedelayneuralnetworks |