ABSTRACT
In today’s finance-driven world, forecasting future results based on previous data and trends is very important to make important decisions. The stock market is one of the most prominent applications of forecasting algorithms in which the future price of the stocks can be predicted based on the previous close price of the stock. The manuscript focuses on a comprehensive review of eight different time series models, viz. AR, ARIMA, SARIMA, ARMA, SES, HWES, Prophet, and LSTM. Models are trained on stock price data and a comparative analysis of the models is presented.
