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IsmailMouddenIsmailMoudden
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feat: reorganize project structure and fix LaTeX compilation
- Move all PNG figures to figures/ directory - Update LaTeX file paths to use correct relative paths - Fix syntax errors in English LaTeX file - Successfully compile both French and English reports - Add .gitignore and CHANGELOG.md files - Update README.md with project information Both rapport_siraedge_fr.pdf and rapport_siraedge_en.pdf now compile successfully
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‎.gitignore‎

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# pipenv
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# According to pypa/pipenv#202, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# Financial data files
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*.csv
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*.xlsx
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*.xls
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*.parquet
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*.h5
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*.hdf5
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# Generated figures (keep source code, exclude large binary files)
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# figures/*.png
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# figures/*.jpg
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# figures/*.jpeg
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# figures/*.gif
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# figures/*.svg
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# PDF reports (keep LaTeX source, exclude compiled PDFs)
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# rapport/pdf/*.pdf
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# OS generated files
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.DS_Store
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.DS_Store?
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._*
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.Spotlight-V100
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.Trashes
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ehthumbs.db
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Thumbs.db
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# IDE files
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.vscode/
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.idea/
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*.swp
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*.swo
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*~
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# Logs
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*.log
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logs/
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# Temporary files
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*.tmp
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*.temp
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temp/
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tmp/
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# Backup files
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*.bak
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*.backup
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*.old
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# Local configuration
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config.local.py
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.env.local

‎CHANGELOG.md‎

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# Changelog
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All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [Unreleased]
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### Added
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- Initial release of SiraEdge Portfolio Optimization Module
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- 7 portfolio optimization models implementation
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- Machine learning integration with Ridge Regression
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- Comprehensive backtesting framework
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- LaTeX report generation in French and English
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- Automated figure generation
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- Walk-forward analysis capabilities
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## [1.0.0] - 2025-01-XX
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### Added
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- **Markowitz (Mean-Variance) Optimization**
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- Sharpe ratio maximization
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- Risk-return balancing
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- Efficient frontier visualization
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- **Risk Parity Model**
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- Equal risk contribution across assets
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- Robust to return uncertainty
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- Natural diversification properties
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- **Monte Carlo Simulation**
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- 10,000 random portfolio generation
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- Solution space exploration
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- Efficient frontier validation
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- **Black-Litterman Model**
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- Market equilibrium integration
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- Investor views incorporation
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- Institutional-grade approach
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- **Machine Learning Predictor**
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- Ridge regression implementation
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- Technical indicators analysis (RSI, momentum, volatility)
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- Return forecasting capabilities
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- **Hybrid Model**
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- Risk Parity + ML signals combination
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- Core-satellite approach
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- Stable foundation with smart opportunism
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- **Custom Metrics Optimization**
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- Multi-objective optimization
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- Sharpe + Stability + MDD + Turnover
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- Investor preference adaptation
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### Technical Features
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- **Data Management**
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- Automatic data download via yfinance
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- Fallback to synthetic data
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- Technical indicators calculation
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- Dynamic correlation analysis
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- **Backtesting Framework**
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- Rolling window analysis (252 days)
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- Monthly rebalancing
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- Transaction costs simulation (5 bps)
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- Comprehensive performance metrics
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- **Performance Metrics**
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- Classic: Sharpe, Sortino, Calmar ratios
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- Advanced: Weight stability, turnover, diversification
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- Risk measures: Volatility, max drawdown, VaR
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- **Documentation**
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- Bilingual LaTeX reports (FR/EN)
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- Comprehensive README files
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- Code documentation and examples
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- Educational content and explanations
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### Infrastructure
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- **CI/CD Pipeline**
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- Automated testing across Python versions
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- Security scanning with Bandit and Safety
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- Code quality checks with flake8
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- Automated releases and deployments
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- **Repository Management**
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- Issue templates for bugs and features
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- Contribution guidelines
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- Code of conduct
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- Automated dependency updates
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## [0.9.0] - 2025-01-XX
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### Added
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- Initial development version
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- Core optimization algorithms
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- Basic backtesting framework
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- Documentation structure
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## [0.8.0] - 2025-01-XX
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### Added
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- Machine learning integration
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- Advanced metrics calculation
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- Performance optimization
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- Enhanced error handling
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## [0.7.0] - 2025-01-XX
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### Added
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- Walk-forward analysis
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- Transaction costs simulation
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- Comprehensive reporting
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- Figure generation automation
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## [0.6.0] - 2025-01-XX
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### Added
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- Hybrid model implementation
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- Custom metrics optimization
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- Advanced visualization
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- LaTeX report generation
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## [0.5.0] - 2025-01-XX
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### Added
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- Black-Litterman model
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- Monte Carlo simulation
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- Risk parity implementation
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- Basic backtesting
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## [0.4.0] - 2025-01-XX
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### Added
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- Markowitz optimization
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- Data utilities
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- Technical indicators
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- Basic structure
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## [0.3.0] - 2025-01-XX
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### Added
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- Project foundation
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- Basic architecture
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- Dependencies setup
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- Initial documentation
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## [0.2.0] - 2025-01-XX
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### Added
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- Repository structure
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- License setup
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- Basic README
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- Project configuration
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## [0.1.0] - 2025-01-XX
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### Added
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- Initial project setup
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- Git repository
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- Basic file structure
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- Project naming
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---
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## Version History
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- **1.0.0**: First stable release with all core features
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- **0.9.0**: Feature-complete beta version
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- **0.8.0**: ML integration and advanced features
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- **0.7.0**: Backtesting and reporting
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- **0.6.0**: Hybrid models and custom metrics
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- **0.5.0**: Advanced optimization models
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- **0.4.0**: Core optimization algorithms
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- **0.3.0**: Project foundation
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- **0.2.0**: Repository setup
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- **0.1.0**: Initial project creation
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## Contributing
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Please read [CONTRIBUTING.md](CONTRIBUTING.md) for details on our code of conduct and the process for submitting pull requests.
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## License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

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