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Multi-level Pattern Prediction of Unstructured Financial Data: Extended Hidden Markov Decision Model Prediction System - Softcover
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Predicting the future is one aspect in designing profitable day trading strategies. Technical analysis analyses price, volume and other market information, whereas fundamental analysis looks at the facts of the company, market, currency or commodity. Most large brokerage, trading group, or financial institutions will typically have both a technical analysis and fundamental analysis team. Technical analysis is considered for the research work. The design of HMDM based stock market trend prediction system and the EHHMM for predicting the future trend of the CBOE and Nigerian 7up bottling company data is presented in this research work. Features are extracted from the historical CBOE closing price data. Extracted features are used to generate the prediction. HHMMs are useful in applications dealing with sequences of symbols. It is observed by study that the EHMDM based system is more accurate than the HMDM based system. It was observed that the EHMDM combined with EST prediction system produces a better accuracy. The HMDM combined with MAT prediction system, with hidden states, produced a lower accuracy. It can be concluded from the present study that prediction system with EHMDM
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Multi-level Pattern Prediction of Unstructured Financial Data
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LAP LAMBERT Academic Publishing Aug 2019, 2019
ISBN 10: 6200258171
ISBN 13: 9786200258175
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Predicting the future is one aspect in designing profitable day trading strategies. Technical analysis analyses price, volume and other market information, whereas fundamental analysis looks at the facts of the company, market, currency or commodity. Most large brokerage, trading group, or financial institutions will typically have both a technical analysis and fundamental analysis team. Technical analysis is considered for the research work. The design of HMDM based stock market trend prediction system and the EHHMM for predicting the future trend of the CBOE and Nigerian 7up bottling company data is presented in this research work. Features are extracted from the historical CBOE closing price data. Extracted features are used to generate the prediction. HHMMs are useful in applications dealing with sequences of symbols. It is observed by study that the EHMDM based system is more accurate than the HMDM based system. It was observed that the EHMDM combined with EST prediction system produces a better accuracy. The HMDM combined with MAT prediction system, with hidden states, produced a lower accuracy. It can be concluded from the present study that prediction system with EHMDM 140 pp. Englisch. Seller Inventory # 9786200258175
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Multi-level Pattern Prediction of Unstructured Financial Data
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ISBN 13: 9786200258175
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Akinbode KayodeAkinbode Kayode Babatunde graduated from computer science department at the university of Ilorin with B.Sc (Second class lower). I did my M.Sc and PhD at the University of Ibadan. My field of interest are Machine learn. Seller Inventory # 385886518
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Multi-level Pattern Prediction of Unstructured Financial Data
Published by
LAP LAMBERT Academic Publishing Aug 2019, 2019
ISBN 10: 6200258171
ISBN 13: 9786200258175
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Predicting the future is one aspect in designing profitable day trading strategies. Technical analysis analyses price, volume and other market information, whereas fundamental analysis looks at the facts of the company, market, currency or commodity. Most large brokerage, trading group, or financial institutions will typically have both a technical analysis and fundamental analysis team. Technical analysis is considered for the research work. The design of HMDM based stock market trend prediction system and the EHHMM for predicting the future trend of the CBOE and Nigerian 7up bottling company data is presented in this research work. Features are extracted from the historical CBOE closing price data. Extracted features are used to generate the prediction. HHMMs are useful in applications dealing with sequences of symbols. It is observed by study that the EHMDM based system is more accurate than the HMDM based system. It was observed that the EHMDM combined with EST prediction system produces a better accuracy. The HMDM combined with MAT prediction system, with hidden states, produced a lower accuracy. It can be concluded from the present study that prediction system with EHMDMVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch. Seller Inventory # 9786200258175
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Multi-level Pattern Prediction of Unstructured Financial Data: Extended Hidden Markov Decision Model Prediction System
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ISBN 13: 9786200258175
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Paperback. Condition: Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock. Seller Inventory # zk6200258171
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Multi-level Pattern Prediction of Unstructured Financial Data | Extended Hidden Markov Decision Model Prediction System
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Taschenbuch. Condition: Neu. Multi-level Pattern Prediction of Unstructured Financial Data | Extended Hidden Markov Decision Model Prediction System | Kayode Akinbode | Taschenbuch | 140 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200258175 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 117328904
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Multi-level Pattern Prediction of Unstructured Financial Data : Extended Hidden Markov Decision Model Prediction System
Published by
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200258171
ISBN 13: 9786200258175
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Predicting the future is one aspect in designing profitable day trading strategies. Technical analysis analyses price, volume and other market information, whereas fundamental analysis looks at the facts of the company, market, currency or commodity. Most large brokerage, trading group, or financial institutions will typically have both a technical analysis and fundamental analysis team. Technical analysis is considered for the research work. The design of HMDM based stock market trend prediction system and the EHHMM for predicting the future trend of the CBOE and Nigerian 7up bottling company data is presented in this research work. Features are extracted from the historical CBOE closing price data. Extracted features are used to generate the prediction. HHMMs are useful in applications dealing with sequences of symbols. It is observed by study that the EHMDM based system is more accurate than the HMDM based system. It was observed that the EHMDM combined with EST prediction system produces a better accuracy. The HMDM combined with MAT prediction system, with hidden states, produced a lower accuracy. It can be concluded from the present study that prediction system with EHMDM. Seller Inventory # 9786200258175
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