Quantum and Classical Machine Learning in Decentralized Finance: Comparative Evidence from Multi-Asset Backtesting of Automated Market Makers
“Our analysis encompasses classical ML models (Random Forest, Gradient Boosting, Logistic Regression), pure quantum models (VQE Classifier, QNN, QSVM), hybrid quantum-classical models (QASA Hybrid, QASA Sequence, QuantumRWKV), and transformer models.”
AssetCryptospot crypto
StrategyMarket making
TechniqueTransformertree ensemble
ClaimSharpe ratio
Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe
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