From Portfolio Optimization to Quantum Blockchain and Security: A Systematic Review of Quantum Computing in Finance

ArXiv ID: 2307.01155 “View on arXiv”

Authors: Unknown

Abstract

In this paper, we provide an overview of the recent work in the quantum finance realm from various perspectives. The applications in consideration are Portfolio Optimization, Fraud Detection, and Monte Carlo methods for derivative pricing and risk calculation. Furthermore, we give a comprehensive overview of the applications of quantum computing in the field of blockchain technology which is a main concept in fintech. In that sense, we first introduce the general overview of blockchain with its main cryptographic primitives such as digital signature algorithms, hash functions, and random number generators as well as the security vulnerabilities of blockchain technologies after the merge of quantum computers considering Shor’s quantum factoring and Grover’s quantum search algorithms. We then discuss the privacy preserving quantum-resistant blockchain systems via threshold signatures, ring signatures, and zero-knowledge proof systems i.e. ZK-SNARKs in quantum resistant blockchains. After emphasizing the difference between the quantum-resistant blockchain and quantum-safe blockchain we mention the security countermeasures to take against the possible quantumized attacks aiming these systems. We finalize our discussion with quantum blockchain, efficient quantum mining and necessary infrastructures for constructing such systems based on quantum computing. This review has the intention to be a bridge to fill the gap between quantum computing and one of its most prominent application realms: Finance. We provide the state-of-the-art results in the intersection of finance and quantum technology for both industrial practitioners and academicians.

Keywords: Quantum Computing, Portfolio Optimization, Blockchain Security, Monte Carlo Methods, Quantum-Resistant Cryptography, Cross-Asset (General Finance)

Complexity vs Empirical Score

• Math Complexity: 8.5/10
• Empirical Rigor: 3.0/10
• Quadrant: Lab Rats
• Why: The paper presents advanced mathematical concepts like quantum superposition, entanglement, and algorithms (Shor’s, Grover’s), but it is a systematic review that focuses on theoretical foundations and literature survey rather than providing backtest-ready implementations or empirical datasets.

  flowchart TD
    A["Research Goal: Bridge gap between Quantum Computing and Finance"] --> B["Methodology: Systematic Review"]
    B --> C["Key Application Areas Analyzed"]
    C --> D["Portfolio Optimization &<br>Monte Carlo Derivative Pricing"]
    C --> E["Blockchain Security &<br>Quantum-Resistant Cryptography"]
    C --> F["Fraud Detection"]
    D --> G["Findings: Potential for Speedup in<br>Financial Modeling & Optimization"]
    E --> H["Findings: Urgent need for<br>Post-Quantum Cryptography PQC in Fintech"]
    F --> G
    G --> I["Outcome: State-of-the-art<br>Intersection of Quantum Tech & Finance"]
    H --> I