Financial Forecasting Using Machine Learning and Mathematical Models

In this study, we forecast Iran's stock market performance (۲۰۰۸-۲۰۱۹) using data mining and time series methods. Our data mining approach employs five algorithms: random forest, k nearest neighbor, support vector machine, artificial neural network, and gradient boosting. In the time series domain, we utilize ARIMA models. By synergizing these techniques, we offer a comprehensive outlook on Iranian stock trends, merging data mining's algorithmic strength with time series' temporal insights.

کلیدواژه ها:

Data Mining ، ARIMA Models ، Time Series ، Stock Markets