Forecasting Crude Oil Prices Using Reservoir Computing Models
Kaushal Kumar
Accurate crude oil price prediction is crucial for financial decision-making.
We propose a novel reservoir computing model for forecasting crude oil prices.
It outperforms popular deep learning methods in most scenarios, as demonstrated
through rigorous evaluation using daily closing price data from major stock
market indices. Our model's competitive advantage is further validated by
comparing it with recent deep-learning approaches. This study introduces
innovative reservoir computing models for predicting crude oil prices, with
practical implications for financial practitioners. By leveraging advanced
techniques, market participants can enhance decision-making and gain valuable
insights into crude oil market dynamics.