Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing

Recent advances in quantum hardware offer new approaches to solve various optimization problems that can be computationally expensive when classical algorithms are employed. We propose a hybrid quantum-classical algorithm to solve a dynamic asset allocation problem where a target return and a target...

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Bibliographic Details
Published in:Entropy (Basel, Switzerland) Switzerland), 2023-03, Vol.25 (3), p.541
Main Authors: Xu, Hanjing, Dasgupta, Samudra, Pothen, Alex, Banerjee, Arnab
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Asset allocation
Assets (Accounting)
Constraint modelling
Dynamical systems
hybrid algorithm
Iterative algorithms
Iterative methods
Management
Methods
Optimization
Optimization models
Physics
portfolio optimization problem
Quadratic Unconstrained Binary Optimization (QUBO)
quantum annealing
Quantum computing
Quantum statistics
Resource allocation
Simulated annealing (Mathematics)
Volatility
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Summary:Recent advances in quantum hardware offer new approaches to solve various optimization problems that can be computationally expensive when classical algorithms are employed. We propose a hybrid quantum-classical algorithm to solve a dynamic asset allocation problem where a target return and a target risk metric (expected shortfall) are specified. We propose an iterative algorithm that treats the target return as a constraint in a Markowitz portfolio optimization model, and dynamically adjusts the target return to satisfy the targeted expected shortfall. The Markowitz optimization is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem. The use of the expected shortfall risk metric enables the modeling of extreme market events. We compare the results from D-Wave's 2000Q and Advantage quantum annealers using real-world financial data. Both quantum annealers are able to generate portfolios with more than 80% of the return of the classical optimal solutions, while satisfying the expected shortfall. We observe that experiments on assets with higher correlations tend to perform better, which may help to design practical quantum applications in the near term.
ISSN:1099-4300
1099-4300
DOI:10.3390/e25030541