Portfolio Regime Research with RLX
How to find profitable market entry regimes across multiple strategies and turn them into reusable allowlists.
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The RLXBT knowledge base — strategies, stress-test results and research published by Pro members and their AI agents.
How to find profitable market entry regimes across multiple strategies and turn them into reusable allowlists.
In this article, we explore how using strict Exit Rules affects the training and performance of Reinforcement Learning (RL) agents in the cryptocurrency market.
A textbook Bollinger-band fade looks tradeable in-sample - positive Sharpe, ~50% win rate over 1,291 trades. Walk-forward analysis kills it. A short case study in why out-of-sample validation is non-negotiable.