Big Data Analytics and Business Architecture of Indian Stock Market: Predictive Analytics of the Indian Stock Market Movements – Applications of Machine Learning and Artificial Intelligence - Couverture souple

Marxia Oli, Sigo; Selvam, Murugesan

9786200586346: Big Data Analytics and Business Architecture of Indian Stock Market: Predictive Analytics of the Indian Stock Market Movements – Applications of Machine Learning and Artificial Intelligence

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ISBN 10 : 6200586349 ISBN 13 : 9786200586346

Editeur : LAP LAMBERT Academic Publishing, 2020

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This book examines the prediction of stock market movements of India using big data analytics. Stock markets have shifted from the guiding principle of standard finance into behavioral finance. Forecasting is one of the classic issues since the stock markets are volatile, stochastic and non-linear in nature. The values of Momentum, Relative Strength Index, Williams %R and Commodity Channel Index indicated both bullish and bearish trends for BSE-Sensex and NSE-Nifty stock indices which were rampant and robust during the study period. This phenomenon negates the Efficient Market Hypothesis, but it confirmed the existence of Random Walk Theory in the realm of capital market movements. One of the neural network methods, the k-nn algorithm exhibited a higher predictive accuracy than the logistic regression approach. The business architecture and market value of company stocks are changing in every millisecond. The close correlation between the predicted and the actual values indicated that deep learning methods such as Machine Learning and Artificial Neural Networks were more powerful tools in the stock price prediction and helped the investors to make intelligent investment decisions.

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�diteur: LAP LAMBERT Academic Publishing
Date d'�dition: 2020
Langue: anglais
ISBN 10: 6200586349
ISBN 13: 9786200586346
Reliure: Broch�
Nombre de pages: 232
Coordonn�es du fabricant: non disponible
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Big Data Analytics and Business Architecture of Indian Stock Market

Sigo Marxia Oli|Murugesan Selvam

Edit� par LAP LAMBERT Academic Publishing, 2020

ISBN 10 : 6200586349 ISBN 13 : 9786200586346

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Marxia Oli SigoMarxia Oli Sigo is an Assistant Prof., Department of Humanities and Social Sciences, National Institute of Technology Sikkim, India. He has pursued his Doctoral Program in Management.Murugesan Selvam is Dean, Faculty o. N� de r�f. du vendeur 385895821

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Big Data Analytics and Business Architecture of Indian Stock Market

Sigo Marxia Oli

Edit� par LAP LAMBERT Academic Publishing Feb 2020, 2020

ISBN 10 : 6200586349 ISBN 13 : 9786200586346

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book examines the prediction of stock market movements of India using big data analytics. Stock markets have shifted from the guiding principle of standard finance into behavioral finance. Forecasting is one of the classic issues since the stock markets are volatile, stochastic and non-linear in nature. The values of Momentum, Relative Strength Index, Williams %R and Commodity Channel Index indicated both bullish and bearish trends for BSE-Sensex and NSE-Nifty stock indices which were rampant and robust during the study period. This phenomenon negates the Efficient Market Hypothesis, but it confirmed the existence of Random Walk Theory in the realm of capital market movements. One of the neural network methods, the k-nn algorithm exhibited a higher predictive accuracy than the logistic regression approach. The business architecture and market value of company stocks are changing in every millisecond. The close correlation between the predicted and the actual values indicated that deep learning methods such as Machine Learning and Artificial Neural Networks were more powerful tools in the stock price prediction and helped the investors to make intelligent investment decisions. 232 pp. Englisch. N� de r�f. du vendeur 9786200586346

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Big Data Analytics and Business Architecture of Indian Stock Market : Predictive Analytics of the Indian Stock Market Movements � Applications of Machine Learning and Artificial Intelligence

Sigo Marxia Oli

Edit� par LAP LAMBERT Academic Publishing, 2020

ISBN 10 : 6200586349 ISBN 13 : 9786200586346

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book examines the prediction of stock market movements of India using big data analytics. Stock markets have shifted from the guiding principle of standard finance into behavioral finance. Forecasting is one of the classic issues since the stock markets are volatile, stochastic and non-linear in nature. The values of Momentum, Relative Strength Index, Williams %R and Commodity Channel Index indicated both bullish and bearish trends for BSE-Sensex and NSE-Nifty stock indices which were rampant and robust during the study period. This phenomenon negates the Efficient Market Hypothesis, but it confirmed the existence of Random Walk Theory in the realm of capital market movements. One of the neural network methods, the k-nn algorithm exhibited a higher predictive accuracy than the logistic regression approach. The business architecture and market value of company stocks are changing in every millisecond. The close correlation between the predicted and the actual values indicated that deep learning methods such as Machine Learning and Artificial Neural Networks were more powerful tools in the stock price prediction and helped the investors to make intelligent investment decisions. N� de r�f. du vendeur 9786200586346

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Big Data Analytics and Business Architecture of Indian Stock Market

Sigo Marxia Oli

Edit� par LAP LAMBERT Academic Publishing Feb 2020, 2020

ISBN 10 : 6200586349 ISBN 13 : 9786200586346

Neuf Taschenbuch

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Neuware -This book examines the prediction of stock market movements of India using big data analytics. Stock markets have shifted from the guiding principle of standard finance into behavioral finance. Forecasting is one of the classic issues since the stock markets are volatile, stochastic and non-linear in nature. The values of Momentum, Relative Strength Index, Williams %R and Commodity Channel Index indicated both bullish and bearish trends for BSE-Sensex and NSE-Nifty stock indices which were rampant and robust during the study period. This phenomenon negates the Efficient Market Hypothesis, but it confirmed the existence of Random Walk Theory in the realm of capital market movements. One of the neural network methods, the k-nn algorithm exhibited a higher predictive accuracy than the logistic regression approach. The business architecture and market value of company stocks are changing in every millisecond. The close correlation between the predicted and the actual values indicated that deep learning methods such as Machine Learning and Artificial Neural Networks were more powerful tools in the stock price prediction and helped the investors to make intelligent investment decisions.Books on Demand GmbH, �berseering 33, 22297 Hamburg 232 pp. Englisch. N� de r�f. du vendeur 9786200586346

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