Study of Effectiveness of Time Series Modeling (Arima) in Forecasting Stock Prices

Prapanna Mondal · Labani Shit · Saptarsi Goswami

288 citations0/0 files storedInternational Journal of Computer Science Engineering and Applications

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Stock Market Forecasting Methods Forecasting Techniques and Applications Time Series Analysis and Forecasting

Abstract

Stock price prediction has always attracted interest because of the direct financial benefit and the associated complexity.From our literature review, we felt the need of a study having sector specific analysis with a broad range of stocks.In this paper, we have conducted a study on the effectiveness of Autoregressive Integrated Moving Average (ARIMA)model, on fifty six Indian stocks from different sectors.We have chosen ARIMA model, because of its simplicity and wide acceptability of the model.We also have studied the effect on prediction accuracy based on various possible previous period data taken. The comparison and parameterization of the ARIMA model have been done using Akaike information criterion (AIC). The contribution of the paper , are a) coverage of a good number of Indian stocks b) Analysis of the models based on sectors c) Analysis of prediction accuracy based on the varying span of previous period data.

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2007Model Based Inference in the Life Sciences: A Primer on Evidence 1993Forecasting With Dynamic Regression Models.2009Model Based Inference in the Life Sciences: A Primer on Evidence

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