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Cover: 9786204190921 | Accurately Forecasting Stock Prices using LSTM and GRU Neural Networks
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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
Taschenbuch von Armin Lawi (u. a.)
Sprache: Englisch

35,45 €*

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Lieferzeit 4-7 Werktage

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Beschreibung
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.
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.
Über den Autor
Armin Lawi é o Chefe do Departamento de Informática da Universidade de Hasanuddin, Indonésia. Recebeu o Bacharelato em Matemática na Universidade Hasanuddin, Mestrado em Ciência Informática e Engenharia da Comunicação pela Universidade Kyushu, e Doutoramento em Ciência Informática e Engenharia de Sistemas pelo Instituto de Tecnologia Kyushu, Japão.
Details
Erscheinungsjahr: 2021
Fachbereich: Betriebswirtschaft
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Taschenbuch
ISBN-13: 9786204190921
ISBN-10: 620419092X
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Lawi, Armin
Kurnia, Eka
Hersteller: LAP LAMBERT Academic Publishing
Maße: 220 x 150 x 4 mm
Von/Mit: Armin Lawi (u. a.)
Erscheinungsdatum: 30.07.2021
Gewicht: 0,096 kg
Artikel-ID: 120491283
Über den Autor
Armin Lawi é o Chefe do Departamento de Informática da Universidade de Hasanuddin, Indonésia. Recebeu o Bacharelato em Matemática na Universidade Hasanuddin, Mestrado em Ciência Informática e Engenharia da Comunicação pela Universidade Kyushu, e Doutoramento em Ciência Informática e Engenharia de Sistemas pelo Instituto de Tecnologia Kyushu, Japão.
Details
Erscheinungsjahr: 2021
Fachbereich: Betriebswirtschaft
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Taschenbuch
ISBN-13: 9786204190921
ISBN-10: 620419092X
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Lawi, Armin
Kurnia, Eka
Hersteller: LAP LAMBERT Academic Publishing
Maße: 220 x 150 x 4 mm
Von/Mit: Armin Lawi (u. a.)
Erscheinungsdatum: 30.07.2021
Gewicht: 0,096 kg
Artikel-ID: 120491283
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