{
  "as_of": "2026-10-02",
  "status_note": "Search in progress: more entries coming from Video_Scrap",
  "entries": [
    {
      "id": "ml4t-jansen-3e",
      "name": "Machine Learning for Trading, 3rd ed. (Stefan Jansen)",
      "type": "repo",
      "source": "github.com/stefan-jansen/machine-learning-for-trading, MIT, ~21.2K stars; found via Herman Trading (@RHerman) X post; cloned 2026-10-01 21:04 AEST",
      "box_path": "/workspace/ml4t_review/ (review: /workspace/ml4t_review/REVIEW.md)",
      "what_it_does": "Book code: 484 notebooks over 27 chapters. Covers triple-barrier and meta-labels, regime models, XGBoost/LightGBM/CatBoost, deep learning, Chronos forecasting, RL, purged walk-forward CV, Deflated Sharpe/PSR overfitting checks, and transaction costs. Also ships 6 early ml4t-* PyPI packages.",
      "nq_useful": "maybe",
      "verdict_note": "Not a strategy source: there's no 1-minute or session logic, and the futures case study is daily. Most useful as an overfitting gate (Deflated Sharpe + purged walk-forward) beside IS/OOS/HO, then possibly a LightGBM meta-label filter on existing ORB/SMT entries. Nothing has been run or installed yet and there are no results. David's note: 'This could be powerful.'",
      "found_date": "2026-10-01",
      "link": "/dev/farm-ml-models.html#ml4t-jansen-repo"
    },
    {
      "id": "hermes-agent-nous",
      "name": "Hermes Agent (Nous Research)",
      "type": "library",
      "source": "github.com/NousResearch/hermes-agent; docs hermes-agent.nousresearch.com",
      "box_path": "Runs as the farm's Hermie bots on PC1, PC3, PC4",
      "what_it_does": "Open-source self-improving AI agent: saves successful workflows as skills, improves them in use, persistent memory, cron jobs, Telegram gateway. Learns how to run the work; it does not train on price data.",
      "nq_useful": "yes",
      "verdict_note": "Being wired in as the All-in-One self-improving loop runner (2026-10-02): Hermie proposes a change, the All-in-One backtests it IS/OOS/holdout net of commissions, and a fixed gate keeps or rejects. ML tools (overfitting check, trade filter) sit inside the loop.",
      "found_date": "2026-10-02"
    },
    {
      "id": "hermes-ai-mt4-ea",
      "name": "Hermes AI (MT4 expert advisor)",
      "type": "model",
      "source": "mql5.com/en/market/product/155377 ($219); review fxroboteasy.com/experts/hermes-ai",
      "box_path": "not downloaded",
      "what_it_does": "Closed paid MT4 robot, XAUUSD M1-M5 breakout logic.",
      "nq_useful": "no",
      "verdict_note": "Checked, not useful. Third-party backtest -33% ROI, PF 0.56, 38% DD (simulated); MQL5 signal only 2 trades. Not ML, not self-learning, not NQ.",
      "found_date": "2026-10-02"
    },
    {
      "id": "ml-purgedcv",
      "name": "purgedcv (eslazarev/purged-cross-validation)",
      "type": "library: validation / overfitting gate",
      "source": "https://github.com/eslazarev/purged-cross-validation",
      "box_path": "not downloaded",
      "what_it_does": "sklearn-compatible PurgedKFold, WalkForwardSplit, CombinatorialPurgedCV, CSCV + probability_of_backtest_overfitting, PSR, DSR, MinTRL/MinBTL, effective_n_trials, Optuna TrialSharpeRecorder. MIT, 35 stars, last commit 2026-10-01, Py>=3.10, deps numpy/pandas/scipy/sklearn.",
      "nq_useful": "Overfitting gate for the farm: PBO over IS variant matrix, DSR over all optimizer trials, time-based purge/embargo on trade entry/exit timestamps (smoke-tested on Py3.13 with synthetic data).",
      "verdict_note": "Rank 1. Adopt as the gate; pin version and cross-check once against skfolio/RiskLabAI because it is young and single-maintainer.",
      "found_date": "2026-10-02"
    },
    {
      "id": "ml-ml4t-diagnostic-engineer",
      "name": "ml4t-diagnostic + ml4t-engineer",
      "type": "library: validation + labeling/features",
      "source": "https://github.com/ml4t/diagnostic ; https://github.com/ml4t/engineer",
      "box_path": "not downloaded",
      "what_it_does": "Diagnostic: WalkForwardCV, CombinatorialCV, DSR, PBO, RAS, FDR, White's Reality Check, trade diagnostics. Engineer: triple-barrier/ATR-barrier/trend-scanning/meta-labels, 120 features, alt bars. MIT, 33/23 stars, last commits 2026-09-25 AEST, Py 3.12-3.14, polars-first, v0.1.x.",
      "nq_useful": "Meta-label tooling and second-opinion overfitting stats; ML4T book ch.7/16 as manual. Needs pandas->polars conversion.",
      "verdict_note": "Rank 2. Best documented; heavier (56/66 declared deps) and 0.1.x API churn; use in a separate env or borrow functions.",
      "found_date": "2026-10-02"
    },
    {
      "id": "ml-risklabai",
      "name": "RiskLabAI.py",
      "type": "library: Lopez de Prado AFML implementation",
      "source": "https://github.com/RiskLabAI/RiskLabAI.py",
      "box_path": "not downloaded",
      "what_it_does": "triple_barrier, meta_labeling, CUSUM event filters, sample-uniqueness weights, purged k-fold, walk-forward, CPCV (bagged/adaptive), MDI/MDA/SFI, PSR/DSR, PBO, bet sizing. BSD-3, 5 stars, v3.1.0 (2026-08-26), Py 3.12-3.14, pandas-based.",
      "nq_useful": "pandas-native meta-labelling + sample weights for filtering ORB/SMT trades; installs and imports on Py3.13.",
      "verdict_note": "Rank 3. Broadest maintained open AFML port; low star count = little external review, import only needed modules.",
      "found_date": "2026-10-02"
    },
    {
      "id": "ml-optuna",
      "name": "Optuna",
      "type": "library: hyperparameter optimisation",
      "source": "https://github.com/optuna/optuna",
      "box_path": "not downloaded",
      "what_it_does": "Hyperparameter/parameter search with trial logging. MIT, 14,867 stars, last commit 2026-09-30, v5.0.0, Py>=3.9.",
      "nq_useful": "Drive DNA/meta-model tuning while recording every trial for DSR via purgedcv TrialSharpeRecorder.",
      "verdict_note": "Rank 4. Enabler only; without the DSR/PBO gate it increases overfitting.",
      "found_date": "2026-10-02"
    },
    {
      "id": "ml-skfolio",
      "name": "skfolio",
      "type": "library: portfolio optimisation with CPCV",
      "source": "https://github.com/skfolio/skfolio",
      "box_path": "not downloaded",
      "what_it_does": "sklearn-style portfolio optimisation; CombinatorialPurgedCV with purged_size/embargo_size and path recombination, WalkForward. BSD-3, 2,457 stars, last commit 2026-10-01, v1.4.10, Py>=3.10.",
      "nq_useful": "Mature second implementation of CPCV to cross-check purgedcv splits (row-count purge, not time-based).",
      "verdict_note": "Rank 5. Backup/cross-check only; no DSR/PBO found in docs checked; portfolio-focused, pulls cvxpy.",
      "found_date": "2026-10-02"
    }
  ]
}