عنوان : تجزیه و تحلیل مقایسه‌ای روش VARMAو LSTM در پیش‌بینی قیمت سهام
موضوع : مهندسی صنایع
سایر نویسندگان : سرکار خانم محدثه فاتحی ,جناب آقای سید محمد تقی فاطمی قمی (نویسنده مسئول) ,جناب آقای سید محمد رضا کاظمی
کد مقاله : confima3-07370720
ارائه دهنده : محدثه فاتحی
متن چکیده : Today, financial markets are affected by various social and political events. This makes forecasting even more important. Forecasting financial markets help stockholders to sell or buy the stock, when necessary, which leads to increased profits. Since there are many forecasting methods, this paper applies two methods, Vector Autoregressive Moving Average (VARMA) and Long Short-Term Memory (LSTM) for forecasting. Forecasting was done on the stock price data of two Apple and Microsoft companies, which include four features: Open, High, Close, and Low. By comparing these two prediction models using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) criteria, it is concluded that LSTM method is more suitable for stock price prediction than VARMA