Python backtesting

Python :

enorme liste quant

Lire https://mayerkrebs.com/best-backtesting-library-for-python/
cite

VectorBT: fastest backtesting library

Backtesting.py: easiest backtesting library

AlephNull

Backtrader

Bt

Pybacktest

PyAlgoTrade

Zipline

Obtenir les données

Les données historiques financières peuvent être obtenues par :

  • pandas-datareader, Free accounts using pandas-datareader are rate limited and can access a limited number of symbols, approximately 500 at the time the documentation was written
  • Quandl,
  • findatapy, many sources including Quandl, Bloomberg, Yahoo, Google etc.
  • yFinance, somewhere between 250,000 to 400,000+ tickers across all asset types
  • investpy, investpy is a Python package to retrieve data from Investing.com, which provides data retrieval from up to 39952 stocks, 82221 funds, 11403 ETFs, 2029 currency crosses, 7797 indices, 688 bonds, 66 commodities, 250 certificates, and 4697 cryptocurrencies.

Optimisation de portfolio

https://riskfolio-lib.readthedocs.io/en/latest/

Autres outils quant:
Pyfolio
Zipline

https://www.pybroker.com/en/latest/notebooks/9.%20Rebalancing%20Positions.html

https://github.com/10mohi6/portfolio-backtest-python

Lesquels pour calculer une frontière efficiente ?

Liste de projets

https://git.tuu.cat/topics/efficient-frontier?o=desc&s=forks

Numpy, Pandas

https://nbviewer.org/github/rian-dolphin/Efficient-Frontier-Python/blob/main/Markowitz.ipynb
https://www.machinelearningplus.com/machine-learning/portfolio-optimization-python-example/
https://medium.com/@zeng.simonl/the-efficient-frontier-in-python-a1bc9496a0a1
https://www.youtube.com/watch?v=qJ5yCvA5E3Q

https://www.youtube.com/watch?v=f2BCmQBCwDs
https://www.youtube.com/watch?v=naYXfyKC4eM
https://www.youtube.com/watch?v=Isutk-wqJfE

Scipy

https://www.kaggle.com/code/vijipai/lesson-5-mean-variance-optimization-of-portfolios
https://amangupta16.medium.com/portfolio-optimization-using-python-part-1-2-9fd80097a606
https://github.com/tthustla/efficient_frontier/blob/master/Efficient%20_Frontier_implementation.ipynb
https://www.linkedin.com/pulse/efficient-frontier-portfolio-optimisation-inpython-ricky-kim/
https://colab.research.google.com/github/MOSEK/PortfolioOptimization/blob/master/python/notebooks-colab/ch10_robust_optimization_factor.ipynb

PyPortfolioOpt

https://pyportfolioopt.readthedocs.io/en/latest/index.html
https://nekrasovp.github.io/stock-market-portfolio-optimisation.html
https://www.youtube.com/watch?v=CRt1v50UHmo

Pyfolio

pyfolio

Cvxopt

https://notebook.community/gwulfs/research_public/research/Markowitz-Quantopian-Research
https://github.com/psthomas/efficient-frontier/blob/master/efficient_frontier.ipynb
https://plotly.com/python/v3/ipython-notebooks/markowitz-portfolio-optimization/

Scipy, Statsmodel et Cvxopt

https://alphapowertrading.com/quantopian/CAPM_Revisited_01.html



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