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This study analyzed the stock price trends and predicted values of three top market capitalization stocks, namely Reliance Industries Limited, Tata Consultancy Services and HDFC Bank, which are listed in the Bombay Stock Exchange in India

Big Data Analytics-Application of Artificial Neural Network in Forecasting Stock Price Trends in India

Academy of Accounting and Financial Studies Journal, (2018)

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Abstract

The world has become data driven, which highly accentuated the utilization of information technology. The movements of stock markets are influenced, by both the micro as well as macro economic variables including the legal framework and taxation policies of the respective economies. The crux of the issue lies in exactly forecasting the fu...More

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Introduction
  • Big Data becomes the buzzword in the field of technology for some time (Tayal et al, 2018). Siegel (2016) emphasized that a little prediction goes a long way.
  • Neural networks are a class of generalized, non-linear and non-parametric models, developed from the studies of human brain
  • It is one of the data mining tools, which performs better than the conventional statistical tools of financial forecasting.
  • Prediction of stock price movements, being big data, is increasingly difficult due to the prevalence of an element of uncertainties involved with the probable future outcomes (Siegel, 2016).
  • ANN, one of the applications of neural network method, is used in this study, to analyze current price trends and probable future prices of company stocks (Maas, 2017)
Highlights
  • Big Data becomes the buzzword in the field of technology for some time (Tayal et al, 2018). Siegel (2016) emphasized that a little prediction goes a long way
  • Forecasting the movement of stock price of a company and stock index is a classic problem, to all those who are connected to the stock markets
  • Prediction of stock price movements, being big data, is increasingly difficult due to the prevalence of an element of uncertainties involved with the probable future outcomes (Siegel, 2016)
  • The objective of this study is to find out the existing trend and to forecast the future direction of the stock price movements of Reliance Industries Limited, Tata Consultancy Services Limited and HDFC Bank Limited, using artificial neural network
  • The analysis clearly indicates that the stock prices of all the three sample stocks (RIL, Tata Consultancy Services (TCS) and HDFC Bank), varied widely, in tune with price variants, namely opening price, high price, low price and closing price during intra-day transactions, during the study period, on all parameters of descriptive statistics, used in this study
  • This study analyzed the stock price trends and predicted values of three top market capitalization stocks, namely Reliance Industries Limited (RIL), TCS and HDFC Bank, which are listed in the Bombay Stock Exchange in India
Methods
  • The stock of three top companies, namely Reliance Industries Limited (Rs. 5,91,580 crores), Tata Consultancy Services Limited (Rs. 5,60,072 crores) and HDFC Bank Limite (Rs. 4,88,604 crores) were selected, based on the top value in its free-float market capitalization, as on 15-02-2017.
  • These three companies stocks were taken, as sample units, for this study.
  • In order to forecast the stock price trends of Reliance Industries Limited, Tata Consultancy Services Limited and HDFC Bank Limited, the statistical tools, SPSS and Neural Works Predict, were used in the study.
Conclusion
  • This study analyzed the stock price trends and predicted values of three top market capitalization stocks, namely RIL, TCS and HDFC Bank, which are listed in the Bombay Stock Exchange in India.
  • Forecasting of stock market movements become difficult, due to the uncertainties involved, with the future stock prices (Hassan et al, 2007).
  • If and only if the information obtained, relating to the stock prices, were pre-processed efficiently, using the machine learning method like the artificial neural network, the forecasting would become more accurate and the investors could ensure earning capital appreciation, for their stock investments, which would ensure maximization of wealth in the long run.
Tables
  • Table1: DESCRIPTIVE ANALYTICS FOR RIL, TCS AND HDFC BANK STOCK PRICES DURING THE
  • Table2: STOCK PRICE TRENDS FOR RIL, TCS AND HDFC BANK DURING THE PERIOD 2008 TO 2017
Download tables as Excel
Study subjects and analysis
observations: 9904
For each trading day, four strata values were considered. The total observations, used in the study, were 29718 for the 2476 trading days (9904 observations for each stock), which is voluminous in nature and they require machines and human intelligence to process and to draw meaningful inferences (Kohzadi et al, 1996). The holistic view of the stock price trends of Reliance Industries Limited, Tata Consultancy Services and HDFC Bank, is illustrated in Table 2

cases: 3
Big Data processes huge volumes of transactional information in real time (Gupta and Tripathi, 2016). At a particular point of time, there could be trends, cycles and random walk or a combination of these three cases/events, in respect of stock market movements (Snigaroff and Wroblewski, 2011). The closing value of the stock index has been used, as one of the important statistical data, to derive useful information about the current and probable future movement pattern of stock markets (Zhang et al, 2005)

observations: 9904
For each trading day, four strata values were considered. The total observations, used in the study, were 29718 for the 2476 trading days (9904 observations for each stock), which is voluminous in nature and they require machines and human intelligence to process and to draw meaningful inferences (Kohzadi et al, 1996). DESCRIPTIVE ANALYTICS FOR RIL, TCS AND HDFC BANK STOCK PRICES DURING THE

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Author
Marxia Oli Sigo
Marxia Oli Sigo
Murugesan Selvam
Murugesan Selvam
Balasundram Maniam
Balasundram Maniam
Kannaiah Desti
Kannaiah Desti
Chinnadurai Kathiravan
Chinnadurai Kathiravan
Thanikachalam Vadivel
Thanikachalam Vadivel
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