Year: 2025
Type: article
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.
DOI: 10.55041/ijsrem52948
Authors: Nandhini D, Sri Harshini M
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4415073328
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