STOCK PRICE PREDICTION USING TIME SERIES FORECASTING BY MACHINE LEARNING MODELS
Keywords:RIMA, Root mean square error, Finance, Time series, Short term pricing, seasonal decomposition, log decomposition.
It is a highly obvious fact that, the stock market is a fickle beast, and making forecasts may be difficult. Stock prices are impacted by both economic and non-economic variables. Refers to several essential physical, psychological, rational, and so on factors. The stock price is predicted using the autoregressive integrated migration Average (ARIMA) model in this research article. have a model for predicting stock prices. Create and disseminate obtained inventory data from Yahoo Finance on a regular basis. The experimental findings show that ARIMA models may be used to accurately estimate inventory levels and short-term pricing.