Application of Ensemble Machine Learning in the Predictive Data Analytics of Indian Stock Market

Journal Title: Webology - Year 2019, Vol 16, Issue 2

Abstract

The world of today is high frequency data driven and characterized by the application and use of information technology for better business development and decision making. The price movements of stock markets are mainly influenced by micro and macro economic variables, legal framework and taxation policies of the respective economies. The crux of the issue lies in exactly forecasting the future stock price movements of individual firms, based on historical or past prices. Achieving the accuracy for forecasting the market trend has become difficult due to the prevalence of stochastic behavior in the stock market and volatility in the stock prices. This paper analyses the stochasticity of movement pattern of the most volatile, fifty company stocks (in terms of market capitalization) of NSE-Nifty, using ensemble machine learning method. The findings of the study would help the investors, to make rational and well informed investment decisions, to optimize the stock returns by investing in the most valuable stocks.

Authors and Affiliations

Marxia Oli Sigo, Murugesan Selvam, Sankaran Venkateswar and Chinnadurai Kathiravan

Keywords

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  • EP ID EP687823
  • DOI 10.14704/WEB/V16I2/a195
  • Views 158
  • Downloads 0

How To Cite

Marxia Oli Sigo, Murugesan Selvam, Sankaran Venkateswar and Chinnadurai Kathiravan (2019). Application of Ensemble Machine Learning in the Predictive Data Analytics of Indian Stock Market. Webology, 16(2), -. https://europub.co.uk/articles/-A-687823