Ultimate motherload Python packages list for quant trading
This is what I call the mother load of ultimate collection of Python packages and resource for quant and algo trading. They come from a person who has worked with Python for over 10+ years so a HUGE thanks to him for providing this.
Ok so first for timeseries storage, Arctic can be very interesting. It’s build on top of MongoDB and can perform very well. It should support Python 3 very soon https://github.com/manahl/arctic (it was only Python 2 until recently).
Market data are very compressible so it uses lz4 compression
This week Packt Publishing gives free books about machine learning. That should be something interesting for market data analysis
https://www.packtpub.com/packt/offers/free-learnin
I won’t say secretive because Matplotlib is nice for charting. See Sentdex video https://www.youtube.com/playlist?list=PLQVvvaa0QuDc2QjQOkZ4rtLYZVll_sZF
Ok maybe it could be worth to add some of https://pypi.python.org/pypi/yahoo-finance code to Pandas DataReader so it will have cache to DB
https://www.quantstart.com/articles/using-python-ibpy-and-the-interactive-brokers-api-to-automate-trades
Redis is essentialy in memory storage
Mongo documents are stored to disk
$ python –version Python 3.4.3 :: Anaconda 2.3.0 (x86_64)
Use Anaconda as it comes with all scientific stack (Numpy, Pandas, Scikit-Learn…)
Yes pandas, matplotlib, and numpy are compatible with Python 3.4
Scikit-Learn is also Python 3 compatible
Some backtesting tools now
Event driven backtesting with Python http://www.quantstart.com/articles/Event-Driven-Backtesting-with-Python-Part-I
Tradingmachine https://pypi.python.org/pypi/tradingmachine
Python 3 provides a better way to handle unicode characters
print is a function – print(“….”)
https://www.quantopian.com/posts/a-framework-to-manage-bracket-orders-with-sl-tp-and-additional-features-trailingstop-breakeven-expiration-and-advanced-statistics
Prophet – Financial markets analysis framework for programmers https://github.com/Emsu/prophet
C with ctypes
https://docs.python.org/2/library/ctypes.html
You can speedup Python code using Cython, PyPy
https://www.quora.com/How-do-I-speed-up-my-Python-code
I have to go to work
Sorry
some other backtesters
QuantStart Forex https://github.com/mhallsmoore/qsforex QuantStart (Michael Halls-Moore)
backtrader http://www.backtrader.com/ https://github.com/mementum/backtrader llazzaro analyzer https://github.com/llazzaro/analyzer
profitpy https://code.google.com/p/profitpy/
The Python Quant http://quant-platform.com/ http://forpythonquants.com/
Python for Econometrics Kevin Sheppard – univ Oxford http://www.kevinsheppard.com/wiki/Python_for_Econometrics profitpy (Python + Qt4) https://code.google.com/p/profitpy/ itrade (Python + wxPython) http://itrade.sourceforge.net/ 2008
some are quite old and not maintained any more
Some links are not backtester – just some info about Python and trading
Trading with Python – Jev Kuznetsov – twp – tradingwithpython http://tradingwithpython.blogspot.fr/
ffn – Financial Functions for Python http://pmorissette.github.io/ffn/
bt – Flexible Backtesting for Python http://pmorissette.github.io/bt/ https://github.com/pmorissette/bt
Python + R http://www.slideshare.net/lsbardel/python-and-r-for-quantitative-finance-2409526
Backtesting in Python http://financialpython.wordpress.com/
Streaming OUANDA
http://petewerner.blogspot.fr/
OANDA
PyAlgoTrade http://gbeced.github.com/pyalgotrade/
python-backtest https://github.com/3kwa/python-backtest
PyArb https://github.com/harpone/PyArb
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