Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks: A Deep Learning approach for forecasting stock price time-series data in groups - Couverture souple
Synopsis
Stocks or shares are securities that confirm the participation or ownership of a person or entity in a company. Stocks are an attractive investment option because they can generate large profits compared to other businesses, however, the risk can also result in large losses in a short time. Thus, minimizing the risk of loss in stock buying and selling transactions is very crucial and important, and it requires careful attention to stock price movements. Technical factors are one of the methods that are used in learning the prediction of stock price movements through past historical data patterns on the stock market. Therefore, forecasting models using technical factors must be careful, thorough, and accurate, to reduce risk appropriately. This book presents the LSTM and GRU Neural Networks to build stock price forecasting models in groups using technical factors. The investigation uses seven years of benchmark time-series data on daily stock price movements with the same features as several previous related works to show differences in results. Time-series data on stock prices are grouped to follow the general pattern of stock price movements in the stock exchange market.
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks
Edité par
LAP LAMBERT Academic Publishing Jul 2021, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Stocks or shares are securities that confirm the participation or ownership of a person or entity in a company. Stocks are an attractive investment option because they can generate large profits compared to other businesses, however, the risk can also result in large losses in a short time. Thus, minimizing the risk of loss in stock buying and selling transactions is very crucial and important, and it requires careful attention to stock price movements. Technical factors are one of the methods that are used in learning the prediction of stock price movements through past historical data patterns on the stock market. Therefore, forecasting models using technical factors must be careful, thorough, and accurate, to reduce risk appropriately. This book presents the LSTM and GRU Neural Networks to build stock price forecasting models in groups using technical factors. The investigation uses seven years of benchmark time-series data on daily stock price movements with the same features as several previous related works to show differences in results. Time-series data on stock prices are grouped to follow the general pattern of stock price movements in the stock exchange market. 52 pp. Englisch. N° de réf. du vendeur 9786204190921
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks: A Deep Learning approach for forecasting stock price time-series data in groups
Edité par
LAP LAMBERT Academic Publishing, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
Couverture souple
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks: A Deep Learning approach for forecasting stock price time-series data in groups
Edité par
LAP LAMBERT Academic Publishing, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
Couverture souple
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks: A Deep Learning approach for forecasting stock price time-series data in groups
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LAP LAMBERT Academic Publishing, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
Couverture souple
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks
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LAP LAMBERT Academic Publishing, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
Couverture souple
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Lawi ArminArmin Lawi is an Associate Professor of Computer Science at Hasanuddin University, Indonesia where he obtained his Bachelor of Science (B.Sc.) in Mathematics. His Master of Engineering (M.Eng.) and Doctor of Engineering (Dr. N° de réf. du vendeur 499981478
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks
Edité par
LAP LAMBERT Academic Publishing Jul 2021, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -Stocks or shares are securities that confirm the participation or ownership of a person or entity in a company. Stocks are an attractive investment option because they can generate large profits compared to other businesses, however, the risk can also result in large losses in a short time. Thus, minimizing the risk of loss in stock buying and selling transactions is very crucial and important, and it requires careful attention to stock price movements. Technical factors are one of the methods that are used in learning the prediction of stock price movements through past historical data patterns on the stock market. Therefore, forecasting models using technical factors must be careful, thorough, and accurate, to reduce risk appropriately. This book presents the LSTM and GRU Neural Networks to build stock price forecasting models in groups using technical factors. The investigation uses seven years of benchmark time-series data on daily stock price movements with the same features as several previous related works to show differences in results. Time-series data on stock prices are grouped to follow the general pattern of stock price movements in the stock exchange market.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch. N° de réf. du vendeur 9786204190921
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks : A Deep Learning approach for forecasting stock price time-series data in groups
Edité par
LAP LAMBERT Academic Publishing, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Stocks or shares are securities that confirm the participation or ownership of a person or entity in a company. Stocks are an attractive investment option because they can generate large profits compared to other businesses, however, the risk can also result in large losses in a short time. Thus, minimizing the risk of loss in stock buying and selling transactions is very crucial and important, and it requires careful attention to stock price movements. Technical factors are one of the methods that are used in learning the prediction of stock price movements through past historical data patterns on the stock market. Therefore, forecasting models using technical factors must be careful, thorough, and accurate, to reduce risk appropriately. This book presents the LSTM and GRU Neural Networks to build stock price forecasting models in groups using technical factors. The investigation uses seven years of benchmark time-series data on daily stock price movements with the same features as several previous related works to show differences in results. Time-series data on stock prices are grouped to follow the general pattern of stock price movements in the stock exchange market. N° de réf. du vendeur 9786204190921
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Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks | A Deep Learning approach for forecasting stock price time-series data in groups
Edité par
LAP LAMBERT Academic Publishing, 2021
ISBN 10 : 620419092X
ISBN 13 : 9786204190921
Neuf
Taschenbuch
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Taschenbuch. Etat : Neu. Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks | A Deep Learning approach for forecasting stock price time-series data in groups | Armin Lawi (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204190921 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 120491283
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