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Financial Index Tracking via Quantum Computing with Cardinality Constraints

Author

Listed:
  • Samuel Palmer
  • Konstantinos Karagiannis
  • Adam Florence
  • Asier Rodriguez
  • Roman Orus
  • Harish Naik
  • Samuel Mugel

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.

Suggested Citation

  • Samuel Palmer & Konstantinos Karagiannis & Adam Florence & Asier Rodriguez & Roman Orus & Harish Naik & Samuel Mugel, 2022. "Financial Index Tracking via Quantum Computing with Cardinality Constraints," Papers 2208.11380, arXiv.org.
    • Handle: RePEc:arx:papers:2208.11380
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    File URL: http://arxiv.org/pdf/2208.11380
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    Cited by:

    1. Rubio-García, Álvaro & Fernández-Lorenzo, Samuel & García-Ripoll, Juan José & Porras, Diego, 2024. "Accurate solution of the Index Tracking problem with a hybrid simulated annealing algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    2. Martin Vesely, 2023. "Finding the Optimal Currency Composition of Foreign Exchange Reserves with a Quantum Computer," Papers 2303.01909, arXiv.org.

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