The previous demonstrations of optical reservoir computing (ORC) primarily utilized theoretical dynamic systems. Here, we explore the practical application of ORC in analyzing real-world financial datasets. In terms of prediction accuracy, a comparative analysis is conducted between ORC and its conventional counterpart implemented on a desktop. The results indicate that both models exhibit similar performance levels. Notably, the ORC model, equipped with a reasonably sized reservoir state, demonstrates commendable prediction accuracy. We provide valuable insights into the feasibility and effectiveness of ORC in handling real-world time series data, contributing to the broader understanding of its practical applications.