I discuss the development of an online learning system using the Jane Street Real-Time Market Data Forecasting challenge as a practice ground for time-series forecasting. The project involves predicting the responder_6 variable using an ARIMA model, with a focus on adapting to new data by re-training the model whenever a new date_id is encountered. This approach leverages multiprocessing to meet strict time constraints