Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing

Xu, Hanjing; Dasgupta, Samudra; Pothen, Alex; Banerjee, Arnab

doi:10.3390/e25030541

Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing

Journal Article · Tue Mar 21 00:00:00 EDT 2023 · Entropy

DOI:https://doi.org/10.3390/e25030541· OSTI ID:2471374

Xu, Hanjing ^[1]; Dasgupta, Samudra ^[2]; Pothen, Alex ^[1]; ^[3]

Purdue Univ., West Lafayette, IN (United States)
Purdue Univ., West Lafayette, IN (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
Purdue Univ., West Lafayette, IN (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

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.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2471374

Journal Information:: Entropy, Journal Name: Entropy Journal Issue: 3 Vol. 25; ISSN 1099-4300

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

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Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing

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