STOCK PRICE PREDICTION USING TIME SERIES - Couverture souple

Sateesh Kumar, Kanagala

9786206781806: STOCK PRICE PREDICTION USING TIME SERIES

Couverture souple

ISBN 10 : 6206781801 ISBN 13 : 9786206781806

Editeur : LAP LAMBERT Academic Publishing, 2023

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2023
Langue: anglais
ISBN 10: 6206781801
ISBN 13: 9786206781806
Reliure: Broch�
Nombre de pages: 68
Coordonn�es du fabricant: non disponible
Personne responsable: KreGa Onlinehandel GmbH
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STOCK PRICE PREDICTION USING TIME SERIES

Kanagala Sateesh Kumar

Edit� par LAP LAMBERT Academic Publishing Sep 2023, 2023

ISBN 10 : 6206781801 ISBN 13 : 9786206781806

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The ARIMA model and the EXPONENTIAL SMOOTHING model for stock price prediction were given in this book. Each algorithm identifies the stock data set of all five institutions, according to the evaluations of these two models. The ARIMA model test results showed that it can reliably predict stock prices in the short term. This can lead to beneficial investment decisions for stock market speculators. The ARIMA model may be ready to compete with other short-term prediction models based on the findings obtained. A wide range of frequency values can be used using exponential smoothing. The Exponential smoothing approach was chosen for a single time series that followed a pattern in terms of order selection. There are many well-known time series techniques in the ARIMA. The design section of ARIMA was critical, delivering a nearly straight line. 68 pp. Englisch. N� de r�f. du vendeur 9786206781806

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STOCK PRICE PREDICTION USING TIME SERIES

Sateesh Kumar, Kanagala

Edit� par LAP Lambert Academic Publishing, 2023

ISBN 10 : 6206781801 ISBN 13 : 9786206781806

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The ARIMA model and the EXPONENTIAL SMOOTHING model for stock price prediction were given in this book. Each algorithm identifies the stock data set of all five institutions, according to the evaluations of these two models. The ARIMA model test results sho. N� de r�f. du vendeur 1136217304

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STOCK PRICE PREDICTION USING TIME SERIES

Kanagala Sateesh Kumar

Edit� par LAP LAMBERT Academic Publishing Sep 2023, 2023

ISBN 10 : 6206781801 ISBN 13 : 9786206781806

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The ARIMA model and the EXPONENTIAL SMOOTHING model for stock price prediction were given in this book. Each algorithm identifies the stock data set of all five institutions, according to the evaluations of these two models. The ARIMA model test results showed that it can reliably predict stock prices in the short term. This can lead to beneficial investment decisions for stock market speculators. The ARIMA model may be ready to compete with other short-term prediction models based on the findings obtained. A wide range of frequency values can be used using exponential smoothing. The Exponential smoothing approach was chosen for a single time series that followed a pattern in terms of order selection. There are many well-known time series techniques in the ARIMA. The design section of ARIMA was critical, delivering a nearly straight line.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 68 pp. Englisch. N� de r�f. du vendeur 9786206781806

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STOCK PRICE PREDICTION USING TIME SERIES

Kanagala Sateesh Kumar

Edit� par LAP LAMBERT Academic Publishing, 2023

ISBN 10 : 6206781801 ISBN 13 : 9786206781806

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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The ARIMA model and the EXPONENTIAL SMOOTHING model for stock price prediction were given in this book. Each algorithm identifies the stock data set of all five institutions, according to the evaluations of these two models. The ARIMA model test results showed that it can reliably predict stock prices in the short term. This can lead to beneficial investment decisions for stock market speculators. The ARIMA model may be ready to compete with other short-term prediction models based on the findings obtained. A wide range of frequency values can be used using exponential smoothing. The Exponential smoothing approach was chosen for a single time series that followed a pattern in terms of order selection. There are many well-known time series techniques in the ARIMA. The design section of ARIMA was critical, delivering a nearly straight line. N� de r�f. du vendeur 9786206781806

Contacter le vendeur