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A Framework for Empowering Reinforcement Learning Agents with Causal Analysis: Enhancing Automated Cryptocurrency Trading
Designed as the foundational architecture of the trading system, the CausalReinforceNet framework enhances the capabilities of the reinforcement learning agent through causal analysis.
Causal Feature Engineering of Price Directions of Cryptocurrencies using Dynamic Bayesian Networks
The efficacy of the proposed model in predicting cryptocurrency price directions is evaluated from two perspectives.
Modelling Determinants of Cryptocurrency Prices: A Bayesian Network Approach
The ensuing networks are used for causal reasoning and diagnosis, and the results indicate that social media (in particular Twitter data in this study) is the most significant influencing factor of the prices of altcoins.
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