Stock Market Prediction Using Time Series Analysis

Abstract

Stock market is a market that enables seamless exchange of buying and selling of company stocks. Every Stock Exchange has their own Stock Index value. Index is the average value that is calculated by combining several stocks. This helps in representing the entire stock market and predicting the market’s movement over time. The Equity market can have a profound impact on people and the country’s economy as a whole. Therefore, predicting the stock trends in an effective manner can minimize the risk of investing and maximize profit. In our paper, we are using the Time Series Forecasting methodology for predicting and visualizing the predictions. Our focus for prediction will be based on the technical analysis using historic data and ARIMA Model. Autoregressive Integrated Moving Average (ARIMA) model has been used extensively in the field of finance and economics as it is known to be robust, efficient and has a strong potential for short-term share market prediction.

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