Reinforcement Learning-Based Cryptocurrency Portfolio Management Using Soft Actor-Critic and Deep Deterministic Policy Gradient Algorithms

By Kamal Paykan

Published 2025-11-16

Everscope rating

1446.9

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

3 / 5

About this paper

Methodology: Deep Reinforcement Learning with Actor-Critic Algorithms (DDPG and SAC) enhanced with LSTM. Problem types: Portfolio Optimization, Reinforcement Learning, Risk Management, Time Series Forecasting, Sequential Decision-Making.

arXiv:2511.20678 · Paper rankings

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