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Merged
jsboige merged 1 commit into from
May 28, 2026
Merged

refactor(qc): remove ESGF branding from remaining 34 files (#1629 Phase 4) #1654

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2 changes: 1 addition & 1 deletion .github/workflows/catalog-drift.yml
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Expand Up @@ -36,7 +36,7 @@ jobs:

base = 'MyIA.AI.Notebooks'
EXCLUDE_ALWAYS = {'.ipynb_checkpoints', 'obj', 'bin', '__pycache__', '.git'}
EXCLUDE_PED = {'research', 'archive', '_output', 'ESGF', 'examples'}
EXCLUDE_PED = {'research', 'archive', '_output', 'partner-course', 'examples'}
CATALOG_RE = re.compile(r'<!--\s*CATALOG-STATUS\s*\n(.*?)\n\s*-->', re.DOTALL)

for series in sorted(os.listdir(base)):
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6 changes: 5 additions & 1 deletion .gitignore
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Expand Up @@ -643,7 +643,11 @@ MyIA.AI.Notebooks/QuantConnect/TrendStocks*/
MyIA.AI.Notebooks/QuantConnect/TurnOfMonth-Researcher/
MyIA.AI.Notebooks/QuantConnect/VIX-TermStructure-Researcher/
MyIA.AI.Notebooks/QuantConnect/lean.json
MyIA.AI.Notebooks/QuantConnect/ESGF-Workspace/
MyIA.AI.Notebooks/QuantConnect/partner-course-Workspace/

# NuGet build artifacts
MyIA.AI.Notebooks/QuantConnect/partner-course-quant-trading/lean-workspace/**/obj/
MyIA.AI.Notebooks/QuantConnect/partner-course-quant-trading/lean-workspace/**/bin/

# Generated secrets (security - never commit raw tokens)
.secrets/.env.generated
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/GenAI/Vibe-Coding/Claude-Code/docs/INSTALLATION-CLAUDE-CODE.md
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Expand Up @@ -534,7 +534,7 @@ claude mcp add --transport stdio serena -- uvx --from git+https://github.com/ora

**Note** : Utilisez `--context claude-code` pour eviter les conflits avec les outils natifs de Claude Code.

#### 7. QuantConnect (Trading Algorithmique - Cours ESGF)
#### 7. QuantConnect (Trading Algorithmique - Cours partenaire)

Le serveur MCP QuantConnect permet a Claude Code d'interagir directement avec la plateforme QuantConnect : creer des projets, compiler du code, lancer des backtests, analyser les resultats. Indispensable pour le cours de trading algorithmique.

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4 changes: 2 additions & 2 deletions MyIA.AI.Notebooks/QuantConnect/ML-Training-Pipeline/research_what_dl_can_predict.ipynb
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"\n",
"> **Context**: 27+ experiments across 8 architectures (MoE, LSTM, Transformer, PatchTST, iTransformer, Mamba, STGAT, MTGNN) failed to beat daily binary direction prediction on modern financial data, even with strict walk-forward OOS validation and multi-seed verification (4/5 seeds FAIL, seed=42 BEAT was +1.5sigma outlier). This notebook investigates what DL *can* predict, to inform a productive pivot.\n",
"\n",
"**Deadline**: 09/05/2026 | **Epic**: NN #754 | **ESGF**: 19/05/2026\n",
"**Deadline**: 09/05/2026 | **Epic**: NN #754 | **Partner**: 19/05/2026\n",
"\n",
"---\n",
"\n",
Expand Down Expand Up @@ -822,7 +822,7 @@
"<a id='section-3'></a>\n",
"## Section 3: Pivot Options for Epic NN #754\n",
"\n",
"Three strategic pivots ranked by feasibility, evidence strength, and ESGF pedagogical impact."
"Three strategic pivots ranked by feasibility, evidence strength, and partner course pedagogical impact."
]
},
{
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-01-Setup.ipynb
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"> Ce notebook est un **support de cours** a lire ici (GitHub ou Jupyter local).\n",
"> **Ne l'uploadez pas dans QuantConnect Lab** - il n'est pas concu pour y etre execute.\n",
"> \n",
"> **Pour votre projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/` dans votre projet QC Lab, puis cliquez Backtest.\n",
"> **Pour votre projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/` dans votre projet QC Lab, puis cliquez Backtest.\n",
"> \n",
"\n",
"---"
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-02-Platform-Fundamentals.ipynb
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"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-05-Universe-Selection.ipynb
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"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-06-Options-Trading.ipynb
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"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-07-Futures-Forex.ipynb
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Expand Up @@ -59,7 +59,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-09-Order-Types.ipynb
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"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-10-Risk-Portfolio-Management.ipynb
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Expand Up @@ -62,7 +62,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-11-Technical-Indicators.ipynb
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Expand Up @@ -64,7 +64,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-12-Backtesting-Analysis.ipynb
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Expand Up @@ -60,7 +60,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-13-Alpha-Models.ipynb
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Expand Up @@ -59,7 +59,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-14-Portfolio-Construction-Execution.ipynb
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Expand Up @@ -75,7 +75,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-15-Parameter-Optimization.ipynb
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Expand Up @@ -95,7 +95,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-16-Alternative-Data.ipynb
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"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/Python/QC-Py-17-Sentiment-Analysis.ipynb
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Expand Up @@ -94,7 +94,7 @@
"> Le code QCAlgorithm presente ici est a **copier dans `main.py`** de votre projet QuantConnect Lab.\n",
"> Ne tentez pas de faire \"Run All\" -- les imports `AlgorithmImports` n'existent pas en Jupyter local.\n",
">\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `ESGF-2026/templates/`, puis adaptez-le.\n",
"> **Pour demarrer un projet QC** : copiez un `main.py` depuis `projects/` ou `partner-course-quant-trading/templates/`, puis adaptez-le.\n",
"\n",
"---"
]
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2 changes: 1 addition & 1 deletion ...antConnect/partner-course-quant-trading/kit-transitoire/01-ML-RandomForest/research.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# ESGF Kit - Recherche ML RandomForest Sector Rotation\n",
"# Partner Course Kit - Recherche ML RandomForest Sector Rotation\n",
"\n",
"Ce notebook explore l'approche ML RandomForest pour la rotation sectorielle sur 9 ETFs sectoriels americains.\n",
"\n",
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2 changes: 1 addition & 1 deletion ...ks/QuantConnect/partner-course-quant-trading/kit-transitoire/02-ML-XGBoost/research.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# ESGF Kit - Recherche ML XGBoost Sector Rotation\n",
"# Partner Course Kit - Recherche ML XGBoost Sector Rotation\n",
"\n",
"Ce notebook explore l'approche ML XGBoost (Gradient Boosting) pour la rotation sectorielle sur 9 ETFs sectoriels americains.\n",
"\n",
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2 changes: 1 addition & 1 deletion ...onnect/partner-course-quant-trading/kit-transitoire/03-Framework-Composite/research.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# ESGF Kit - Recherche Framework Composite (Alpha Models)\n",
"# Partner Course Kit - Recherche Framework Composite (Alpha Models)\n",
"\n",
"Ce notebook explore l'approche QC Framework avec modele composite combinant deux alpha models :\n",
"1. **SectorMomentum** : Long sectors avec momentum positif au-dessus de SMA200\n",
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4 changes: 2 additions & 2 deletions MyIA.AI.Notebooks/QuantConnect/projects/ForexCarry/research.ipynb
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"text": [
"=== VALIDATION QC CLOUD (ForexCarry project 28657908) ===\n",
"Periode: 2015-01-01 a 2026-05-24\n",
"Cloud ID: 28657908 (ESGF_School org)\n",
"Cloud ID: 28657908 (Partner org)\n",
"\n",
" Test Sharpe CAGR% MaxDD% NetProfit% Trades\n",
" v3e-SPY filter -2.347 -0.307 7.3 -3.444 113\n",
Expand Down Expand Up @@ -1545,7 +1545,7 @@
"\n",
"print('=== VALIDATION QC CLOUD (ForexCarry project 28657908) ===')\n",
"print(f'Periode: 2015-01-01 a 2026-05-24')\n",
"print(f'Cloud ID: 28657908 (ESGF_School org)')\n",
"print(f'Cloud ID: 28657908 (Partner org)')\n",
"print()\n",
"print(qc_results.to_string(index=False))\n",
"print()\n",
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4 changes: 2 additions & 2 deletions MyIA.AI.Notebooks/QuantConnect/projects/HAR-RV-Kelly/research.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Research: ESGF-HAR-RV-Kelly\n",
"# Research: Partner-HAR-RV-Kelly\n",
"\n",
"HAR-RV (Heterogeneous Autoregressive Realized Volatility) avec critere de Kelly sur un portefeuille multi-actifs.\n",
"\n",
Expand All @@ -19,7 +19,7 @@
"\n",
"**Actifs** : SPY, EFA, EEM, TLT, GLD, DBC.\n",
"\n",
"**Calibration cible** : `ESGFHARRVKelly` dans `main.py`"
"**Calibration cible** : `PartnerHARRVKelly` dans `main.py`"
]
},
{
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/projects/TrendFilteredMeanReversion/research.ipynb
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"| H4: Multi-instruments | Position sizing dilue, correlation SPY/QQQ | Sharpe degrade |\n",
"| H5: Retirer filtre regime | Plus de trades bear = falling knives | MaxDD augmente |\n",
"\n",
"### Lecons cles pour le cours ESGF\n",
"### Lecons cles pour le cours partenaire\n",
"\n",
"1. **Un signal rentable ne suffit pas** : le win rate de 73% prouve que le signal\n",
" RSI(2) est valide. Mais si la strategie n'est investie que 15% du temps,\n",
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/projects/TrendStocksLite/research.ipynb
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"- **Stop-loss** : ATR trailing stop par position\n",
"- **Universe dynamique** : Remplacer les 15 tickers fixes par un filtre dollar volume\n",
"\n",
"### Usage pedagogique (Module M2 ESGF)\n",
"### Usage pedagogique (Module M2 (cours partenaire))\n",
"\n",
"Ce notebook est ideal pour le Module 2 (Momentum) car il illustre :\n",
"1. **Trend-following basique** : Faber TAA avec filtres multi-indicateurs\n",
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2 changes: 1 addition & 1 deletion MyIA.AI.Notebooks/QuantConnect/projects/TurnOfMonth/research.ipynb
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"**Strategie archivee.** Sharpe ceiling ~0.13 sur la periode 2015-2026.\n",
"\n",
"**Note importante** : Cette strategie etait marquee \"PENDING\" dans le dashboard\n",
"ESGF-2026 et n'a pas ete activement iteree ou backtestee lors du cycle d'optimisation\n",
"partner-course-quant-trading et n'a pas ete activement iteree ou backtestee lors du cycle d'optimisation\n",
"d'avril 2026. Les resultats ci-dessus proviennent du travail anterieur.\n",
"\n",
"| Metrique | Meilleure version (v2.1) | Plafond structurel |\n",
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6 changes: 3 additions & 3 deletions MyIA.AI.Notebooks/QuantConnect/projects/Vol-Ensemble-Conservative/research.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Research: ESGF-VolEnsemble-Conservative\n",
"# Research: Partner-VolEnsemble-Conservative\n",
"\n",
"Ensemble GARCH(1,1) + HAR(1,5,22) avec positionnement conservateur et filtre de regime.\n",
"\n",
Expand All @@ -17,11 +17,11 @@
"un ciblage de volatilite inverse a 8% annualises (plus conservateur que le GARCH seul a 10%).\n",
"\n",
"Un **filtre de regime** base sur SPY vs SMA200 reduit l'allocation de 50% en marche baissier.\n",
"C'est la plus conservatrice des 3 strategies ESGF.\n",
"C'est la plus conservatrice des 3 strategies partner.\n",
"\n",
"**Actifs** : SPY, EFA, EEM, TLT, GLD, DBC.\n",
"\n",
"**Calibration cible** : `ESGFVolEnsembleConservative` dans `main.py`"
"**Calibration cible** : `PartnerVolEnsembleConservative` dans `main.py`"
]
},
{
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4 changes: 2 additions & 2 deletions MyIA.AI.Notebooks/QuantConnect/projects/Vol-GARCH-Target/research.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Research: ESGF-GARCH-VolTarget\n",
"# Research: Partner-GARCH-VolTarget\n",
"\n",
"GARCH(1,1) volatilite targeting sur un portefeuille multi-actifs.\n",
"\n",
Expand All @@ -16,7 +16,7 @@
"\n",
"**Actifs** : SPY, EFA, EEM, TLT, GLD, DBC (multi-actifs style AQR).\n",
"\n",
"**Calibration cible** : `ESGFGARCHVolTarget` dans `main.py`"
"**Calibration cible** : `PartnerGARCHVolTarget` dans `main.py`"
]
},
{
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4 changes: 2 additions & 2 deletions MyIA.AI.Notebooks/README.md
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Expand Up @@ -42,7 +42,7 @@ GenAI (110 notebooks)
QuantConnect (175 notebooks)
├── Python/ (53) - Cours progressifs QC-Py
├── projects/ (109) - Strategies backtests et ML
└── ESGF-2026/ (7) - Cours ESGF exercices et templates
└── partner-course-quant-trading/ (7) - Cours partenaire exercices et templates

SymbolicAI (92 notebooks)
├── SmartContracts/ (27) - Solidity, Web3, blockchain
Expand Down Expand Up @@ -135,7 +135,7 @@ docker-compose up -d
1. **GenAI** - Toutes les series sauf Orchestration
2. **ML** - Tutoriels .NET + Python Agents
3. **SymbolicAI** - SmartContracts, SemanticWeb
4. **QuantConnect/ESGF-2026/** - Exercices trading
4. **QuantConnect/partner-course-quant-trading/** - Exercices trading

### Expert (120h+)
1. **GenAI/03-Orchestration** + **04-Applications**
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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -135,7 +135,7 @@ Peut-on appliquer les techniques d'IA aux marches financiers ? Cette serie repon

**ML Training Pipeline** -- Pipeline complet d'entrainement et d'evaluation de modeles DL pour le forecasting financier : LSTM, Transformer, iTransformer, PatchTST, Mamba. Donnees crypto panier (10 coins) avec validation walk-forward stricte, evaluation zero-shot de modeles foundation (Chronos-Bolt, Kronos), et baselines comparatives (GARCH, random walk, majority class).

**ESGF-2026** -- Exemples de projets etudiants et notebooks de recherche issus du cours ESGF.
**partner-course-quant-trading** -- Exemples de projets etudiants et notebooks de recherche issus du cours partenaire.

Python | [README detaille](MyIA.AI.Notebooks/QuantConnect/README.md) | [Strategies](MyIA.AI.Notebooks/QuantConnect/projects/README.md)

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Python/ Notebooks pedagogiques
projects/ Strategies backtestees
ML-Training-Pipeline/ Pipeline DL forecasting
ESGF-2026/ Projets etudiants
partner-course-quant-trading/ Projets etudiants
EPF/ Projets transversaux (Python)
IIT/ Information integree (Python)
Config/ Configuration API
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