Enhancing African market predictions: Integrating quantum computing with Echo State Networks

Abstract

The integration of Quantum Computing into Echo State Networks (ESN) materializes in the form of the Quantum Echo State Network (QESN), a methodological innovation that reshapes predictive analytics within the domain of artificial intelligence. This investigation harnesses the novel QESN model alongside traditional ESNs, deploying them within the dynamic and burgeoning financial market of Africa. Our focus zeroes in on the Google Stock Price dataset, which provides a rich tapestry of regional financial activity. The QESN model distinguishes itself by a complex interconnection of qubits that conduct quantum operations, offering a marked amplification of computational capability. The empirical analysis reveals that the QESN model’s predictive prowess substantially exceeds that of its ESN counterpart, achieving an unprecedentedly low Mean Squared Error (MSE) of 0.00021 in forecasting market trends. This exceptional figure redefines the standards of financial prediction models in African markets and establishes the QESN as an instrumental breakthrough, providing unparalleled accuracy in the analysis and prediction of financial data.

Keywords

• Deep learning
• Echo state network
• Quantum computing
• Quantum echo state network
• Reservoir computing
• Prediction