Abstract - The swift expansion of cryptocurrency markets necessitates the assessment of clever and flexible trading strategies. In order to optimize cryptocurrency trading strategies, CryptoTradeMate is an AI-powered backtesting framework that combines machine learning, deep learning, and reinforcement learning with historical and on-chain data. The system reduces overfitting and improves robustness by supporting walk-forward optimization, purged cross-validation, and real-time data ingestion. Results from experiments conducted on Bitcoin, Ethereum, and other assets between 2018 and 2024 show that AI-augmented strategies outperform conventional rule-based approaches in terms of stability and risk-adjusted returns, particularly in times of market volatility. Key Words: risk management, machine learning, reinforcement learning, backtesting, cryptocurrency, on-chain data, and optimization.
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D Nandhini
Sri Harshini M
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
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Nandhini et al. (Sat,) studied this question.
synapsesocial.com/papers/68ec51df42911f61ef8b21ae — DOI: https://doi.org/10.55041/ijsrem52948