The Application of Neural Networks in Stock-Exchange Investing
Název práce: | The Application of Neural Networks in Stock-Exchange Investing |
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Autor(ka) práce: | Ogrodnik, Radoslaw |
Typ práce: | Diploma thesis |
Vedoucí práce: | Buus, Tomáš |
Oponenti práce: | Poborský, František |
Jazyk práce: | English |
Abstrakt: | The experiment performed showed that predicting stock movements accurately with a neural networks is a very challenging task. Even obtaining low error in the training process, does not indicate that one will receive high quality predictions in the future. Similarly potential gain obtained be the network in the analysed period does not have to repeat in the next one. The reason behind, is that situations which occurred in the past, do not have to repeat. Moreover there are numerous factors that may influence index's future behaviour which simply cannot be even taken into account by an artificial model. However, even if it is difficult to create a network which would provide an output accurate enough to be used as an only indicator, neural networks are still an interesting tool and may perform well as a guidance for an investor. |
Klíčová slova: | data generalization ; data overfitting ; neural network creation; radial basis function; multilayer perceptron; stock-exchange forecasting; artificial neural network; market forecasting |
Název práce: | The Application of Neural Networks in Stock-Exchange Investing |
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Autor(ka) práce: | Ogrodnik, Radoslaw |
Typ práce: | Diplomová práce |
Vedoucí práce: | Buus, Tomáš |
Oponenti práce: | Poborský, František |
Jazyk práce: | English |
Abstrakt: | The experiment performed showed that predicting stock movements accurately with a neural networks is a very challenging task. Even obtaining low error in the training process, does not indicate that one will receive high quality predictions in the future. Similarly potential gain obtained be the network in the analysed period does not have to repeat in the next one. The reason behind, is that situations which occurred in the past, do not have to repeat. Moreover there are numerous factors that may influence index's future behaviour which simply cannot be even taken into account by an artificial model. However, even if it is difficult to create a network which would provide an output accurate enough to be used as an only indicator, neural networks are still an interesting tool and may perform well as a guidance for an investor. |
Klíčová slova: | artificial neural network; multilayer perceptron; data overfitting; data generalization; neural network creation; market forecasting; stock-exchange forecasting; radial basis function |
Informace o studiu
Studijní program / obor: | Finance and Accounting for Common Europe |
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Typ studijního programu: | Magisterský studijní program |
Přidělovaná hodnost: | Ing. |
Instituce přidělující hodnost: | Vysoká škola ekonomická v Praze |
Fakulta: | Fakulta financí a účetnictví |
Katedra: | Katedra financí a oceňování podniku |
Informace o odevzdání a obhajobě
Datum zadání práce: | 13. 5. 2015 |
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Datum podání práce: | 30. 9. 2015 |
Datum obhajoby: | 12. 10. 2015 |
Identifikátor v systému InSIS: | https://insis.vse.cz/zp/53022/podrobnosti |