Grover Search for Portfolio Selection

ArXiv ID: 2308.13063 “View on arXiv”

Authors: Unknown

Abstract

We present explicit oracles designed to be used in Grover’s algorithm to match investor preferences. Specifically, the oracles select portfolios with returns and standard deviations exceeding and falling below certain thresholds, respectively. One potential use case for the oracles is selecting portfolios with the best Sharpe ratios. We have implemented these algorithms using quantum simulators.

Keywords: Grover’s Algorithm, Portfolio Selection, Quantum Oracles, Sharpe Ratio, Quantum Computing

Complexity vs Empirical Score

• Math Complexity: 7.5/10
• Empirical Rigor: 2.0/10
• Quadrant: Lab Rats
• Why: The paper leverages advanced quantum algorithms like Grover search and phase estimation, involving substantial mathematical formalism and complexity, but implementation is limited to quantum simulators without real-world data, backtests, or performance metrics.

  flowchart TD
    A["Research Goal<br>Quantum Portfolio Selection"] --> B["Data Input<br>Asset Returns & Volatility"]
    B --> C["Methodology<br>Design Grover Oracles"]
    C --> D["Oracles for Thresholds<br>High Returns & Low Std Dev"]
    D --> E["Computational Process<br>Grover's Algorithm Execution"]
    E --> F["Outcome<br>Optimized Portfolio via Sharpe Ratio"]
    F --> G["Implementation<br>Quantum Simulators"]