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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 - Softcover

 
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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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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  • PublisherLAP LAMBERT Academic Publishing
  • Publication date2020
  • ISBN 10 6200586349
  • ISBN 13 9786200586346
  • BindingPaperback
  • LanguageEnglish
  • Number of pages232

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Sigo Marxia Oli|Murugesan Selvam
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200586349 ISBN 13: 9786200586346
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Condition: 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. Seller Inventory # 385895821

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Taschenbuch. Condition: 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. Seller Inventory # 9786200586346

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Sigo Marxia Oli
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200586349 ISBN 13: 9786200586346
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Taschenbuch. Condition: 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. Seller Inventory # 9786200586346

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Marxia Oli, Sigo/ Selvam, Murugesan
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6200586349 ISBN 13: 9786200586346
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Paperback. Condition: Brand New. 232 pages. 8.66x5.91x0.53 inches. In Stock. Seller Inventory # zk6200586349

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