Quantum Computing for Multi Period Asset Allocation

ArXiv ID: 2410.11997 “View on arXiv”

Authors: Unknown

Abstract

Portfolio construction has been a long-standing topic of research in finance. The computational complexity and the time taken both increase rapidly with the number of investments in the portfolio. It becomes difficult, even impossible for classic computers to solve. Quantum computing is a new way of computing which takes advantage of quantum superposition and entanglement. It changes how such problems are approached and is not constrained by some of the classic computational complexity. Studies have shown that quantum computing can offer significant advantages over classical computing in many fields. The application of quantum computing has been constrained by the unavailability of actual quantum computers. In the past decade, there has been the rapid development of the large-scale quantum computer. However, software development for quantum computing is slow in many fields. In our study, we apply quantum computing to a multi-asset portfolio simulation. The simulation is based on historic data, covariance, and expected returns, all calculated using quantum computing. Although technically a solvable problem for classical computing, we believe the software development is important to the future application of quantum computing in finance. We conducted this study through simulation of a quantum computer and the use of Rensselaer Polytechnic Institute’s IBM quantum computer.

Keywords: Quantum Computing, Portfolio Optimization, Multi-asset Portfolio, Quantum Simulation

Complexity vs Empirical Score

  • Math Complexity: 4.5/10
  • Empirical Rigor: 5.0/10
  • Quadrant: Street Traders
  • Why: The paper applies quantum computing algorithms to portfolio simulation using historical data and covariance matrices, but the mathematical exposition is largely conceptual and lacks deep derivations, while the empirical work involves actual quantum hardware runs and backtest-like simulations, albeit with limited statistical validation.
  flowchart TD
    A["Research Goal<br>Apply Quantum Computing<br>to Multi-Period Asset Allocation"] --> B["Data Preparation<br>Historic Market Data"]
    B --> C["Key Methodology<br>Quantum Simulation<br>& RPI IBM Q Computer"]
    C --> D{"Computational Process<br>Calculate Covariance &<br>Expected Returns"}
    D --> E["Quantum Portfolio Optimization<br>Efficient Frontier Generation"]
    E --> F["Key Findings/Outcomes<br>Feasibility of Quantum Finance<br>Software Development Pathway"]