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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