Forecasting stock market prices using mixed ARIMA model: a case study of Indian pharmaceutical companies

Many investors in order to predict stock prices use various techniques like fundamental analysis and technical sometimes rely on the discussions provided by market analysts. ARIMA is a part of time-series under prediction algorithms, this paper attempts share selected pharmaceutical companies India, listed NIFTY100, using model. A sample size 782 observations from January 1, 2017 December 31, 2019 for each firm has been considered frame ADF test used verify whether data are stationary or not. For model estimation, significant spikes correlogram ACF PACF have observed, many models framed taking different AR MA terms company. After that, 5 best selected, necessary inculcation made adjust choose adjusted based Volatility, R-squared, Akaike Information Criterion. The results could be analyze their in-depth future research efforts.