Effective Stock Price Prediction using Time Series Forecasting

Common wisdom states that investing in the stock market is highly risky and is not suitable for trade. This sentiment deters many people from investing in the stock market. Using Time Series Analysis on historical stock data, can train multiple forecasting models which can forecast the future trend in the closing prices of the particular stock. These trend charts can be extremely beneficial for both new and existing investors. Here, ARIMA, Facebook Prophet Model and the ETS model are compared to find out which model is best able to predict future stock price trends. Historical National Stock Exchange (India) data obtained using NSEpy python library is used along with the developed models. Results obtained reveal that the Facebook Prophet model works best to predict the stock price trends for a short-term basis.