The verified falsification record — reproducible trading strategies, out-of-sample stress tests, and negative findings published with complete code, seeds, and evidence.
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.
SergThe definitive multivariable combo strategy on BTCUSDT 1h, out-of-sample validated under realistic commissions.
SergA guide on using the RLXBT Deep Reinforcement Learning (DQN) engine and MCP integrations to train, evaluate, and predict market signals dynamically using AI agents.
SergRobust 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.
SergSymmetrical 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.
SergA robust volatility breakout strategy on BTCUSDT 1h, gated by Hurst Exponent and Fractal Dimension Index, out-of-sample validated under real fees.
SergA 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.
SergA case study on why profitable trading patterns can still be rejected. Analysis of a 5-candle BTC capitulation bottom that returned +2.45% but severely underperformed the passive market baseline (+179.35%).
SergA 24-bar volatility-clustering persistence signal (ARCH-effect autocorrelation) combined with a weekend-volatility-shock exclusion filter lifts BTCUSDT 1h Sharpe from 0.85 to 1.20 (+114.5% return, 100% OOS-positive walk-forward windows) — plus the full trail of what failed along the way and why it still doesn't work on SOL.
SergFour honest negative results from selective ML, order-book, macro and on-chain research—and the reusable boundaries each failure added to the knowledge base.
SergBTC 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.
SergA deep dive into the quant lifecycle of our trading strategies on the RLXBT Hypothesis Canvas, from zero-fee backtest shocks to maker-execution pivots and zero-correlation portfolio ensembles.
SergHow 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.
SergA manifesto on the shift from manual rule-based scripting to agent-driven pattern extraction and no-code backtesting, detailing a workflow that tests raw market states in seconds.
SergCrowded-long ∩ 15m vol filter: val n=38 mean +66 bp but t=1.41 — louder, not stronger than parent t=1.60. WATCH.
Serg10-name crypto XSMOM R=20/H=5/K=2: val LS t=0.23, hit 46.5%; K=3 no rescue. NO_EDGE.
SergFeature Lab marks lsratio/HIGH actually_tradable. Neural: no incremental vs price MLP. Overlapping val t=4.10; nonoverlap t=1.60; WFE=0.16. WATCH, not a book.
SergBTC top-trader L/S HIGH: val fade t=−2.17 but corr vs global 0.99; incremental γ t=−1.45. Same costume. NO_EDGE.
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