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Time Series Model for Stock Price Forecasting in India

  • A. Mohamed Ashik
  • K. Senthamarai Kannan
Chapter
Part of the Asset Analytics book series (ASAN)

Abstract

National stock exchange is widest and fully automatic trading system in India. Analysis and prediction of stock market time series data have involved considerable interest from the researchers over the last decade. Time series model is an essential tool for a data prediction in future demands. Box–Jenkins method is a forecasting model in time sequence records. Mohamed Ashik and Senthamarai Kannan (2017) applied ARIMA model to forecast in National Stock Price the future closing price of Nifty 50. In this paper, several sectors of Nifty daily closing stock market prices were computed and predicted of stock market fluctuations using Box–Jenkins approach. From the study, it can be observed that the energy sector of R-squared value is (99%) very high and mean absolute percentage error is (0.745) tiny for other sectors of Nifty. Hence, the energy sector would be a minimum risk of investors and increasing fluctuations trend for forthcoming trading days.

Keywords

Stock market National stock exchange Stationary process Box–Jenkins method Error rates 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of StatisticsManonmaniam Sundaranar UniversityTirunelveliIndia

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