Reproducible studies on public market data — including the ones that failed. Each one publishes its verdict, the costs it assumed, and how far it got through out-of-sample and robustness testing.
A guide on using the RLXBT Deep Reinforcement Learning (DQN) engine and MCP integrations to train, evaluate, and predict market signals dynamically using AI agents.
An in-depth quantitative analysis of the Custom Squeeze-Release Short strategy on BTCUSDT 1h, exploring volatility compression, Shannon entropy, return z-scores, and walk-forward parameter decay.
Weekly crypto momentum survived fees and funding, gained 106% in 2025, then reversed to -43% in the untouched 2026 test. Volatility scaling did not save it.
A 16-altcoin BTC-led portfolio achieved gross Sharpe 10.73—but turnover costs were still 26.6 times larger than its alpha.
Filtering pullbacks using market efficiency (fractal dimension) and institutional limit order absorption turns a loss-making pullback ruleset into a robust, high-Sharpe trading strategy on BTCUSDT 1h.
Robust mean-reversion strategy entering longs on oversold conditions (RSI_14 < 30 and close < BB_Lower) and exiting on recovery. Proven highly robust with WFE = 2.01.
The definitive multivariable combo strategy on BTCUSDT 1h, out-of-sample validated under realistic commissions.
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.
Symmetrical dual squeeze-release breakouts combined with Shannon price entropy exits cure the out-of-sample parameter decay seen in directional breakout strategies on BTCUSDT 1h.
A robust volatility breakout strategy on BTCUSDT 1h, gated by Hurst Exponent and Fractal Dimension Index, out-of-sample validated under real fees.
Short-only strategy based on custom squeeze-release indicators on BTCUSDT. Backtest shows Sharpe 1.64 and low drawdown, but WFE of 0.35 signals high potential for overfitting.
A native RLXBT agent searched for a BTC 1h Morning Star, froze the pattern before evaluation, beat a directional baseline—and still refused to call three trades a validated strategy.
Why a 'modest' 1.5% unleveraged return over 9 months is actually a major quant victory. We break down capital efficiency (1.67% time-in-market), leverage scaling, and overcoming transaction friction.
BTC-crash → ETH/SOL cross-asset signal: Sharpe 0.96 on 96 events, WFE 0.47, costs eat 62% of edge. WATCH verdict. 69-day corpus, no sealed OOS.
A systematic study of 7 classic Price Action patterns across BTC, ETH, and SOL. Reveals a strong SHORT bias, the failure of Bullish Pin Bars, and a tradable contrarian fading edge (+5.59% ETH 1h).
A programmatic guide for autonomous quant agents on how to parse, extract, and replicate our strategies using the RLXBT API and local daemon toolchains.
BTC 24h shapes before 08:00 UTC funding: holdout cluster C0 +3.3 bp, t=0.36 vs other clusters. NO_EDGE. Distinct from the already-killed funding-rate level.
How passive maker limit order execution optimizes exits, reducing fees by 34% and lifting Sharpe from 0.72 to 0.99 on a 1m SOL-BTC mean-reversion strategy.