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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Gratis für den Versand innerhalb von/der Deutschland
Versandziele, Kosten & DauerAnbieter: moluna, Greven, Deutschland
Zustand: 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. Bestandsnummer des Verkäufers 385895821
Anzahl: Mehr als 20 verfügbar
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9786200586346
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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. Bestandsnummer des Verkäufers 9786200586346
Anzahl: 1 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 232 pages. 8.66x5.91x0.53 inches. In Stock. Bestandsnummer des Verkäufers zk6200586349
Anzahl: 1 verfügbar