학술논문

Financial Index Tracking via Quantum Computing with Cardinality Constraints
Document Type
Working Paper
Source
Subject
Quantum Physics
Computer Science - Computational Engineering, Finance, and Science
Quantitative Finance - Portfolio Management
Language
Abstract
In this work, we demonstrate how to apply non-linear cardinality constraints, important for real-world asset management, to quantum portfolio optimization. This enables us to tackle non-convex portfolio optimization problems using quantum annealing that would otherwise be challenging for classical algorithms. Being able to use cardinality constraints for portfolio optimization opens the doors to new applications for creating innovative portfolios and exchange-traded-funds (ETFs). We apply the methodology to the practical problem of enhanced index tracking and are able to construct smaller portfolios that significantly outperform the risk profile of the target index whilst retaining high degrees of tracking.
Comment: 8 pages, 8 figures, 4 tables