The Quantum Algorithms Institute (QAI) has partnered with AbaQus and InvestDEFY to enhance financial forecasting models using D-Wave’s quantum annealing systems. This collaboration is focused on optimizing feature selection in machine learning for financial applications, addressing key challenges like data non-stationarity and model overfitting. By refining the selection of critical data points, QAI and its partners aim to streamline predictive model training and boost the efficiency and accuracy of financial forecasting.
Initial trials have demonstrated the potential of quantum annealing in identifying relevant data subsets faster than traditional methods, improving both model performance and computational efficiency. Although full metrics are in development, early results indicate reduced processing times for large datasets, a critical advancement for the financial sector where timely decisions can drive significant outcomes.
This partnership underscores the potential of quantum computing in financial predictive analytics, showcasing how quantum-powered feature selection can create more robust models that adapt better to changing data patterns over time. QAI CEO Louise Turner highlighted quantum annealing’s unique role in “identifying the most relevant data points to inform predictive models more efficiently than classical methods.”
For additional details, you can access the original press release here.
November 12, 2024
