New fast backtesting library

[Sal Abbasi]

I recently released a new backtesting library at https://pypi.org/project/pyqstrat/  

I've been building quant strategies for many years and I spent a lot of time looking for a library that could accelerate the process. I could not find anything that fit my needs, which were that it should be fast, transparent and extensible.  So I ended up writing one for my own needs.

I thought this might be useful to other people as well, so decided to open source it.

The readme is at: 

https://github.com/abbass2/pyqstrat/blob/master/README.rst

Here is a notebook showing you how to get started.

https://github.com/abbass2/pyqstrat/blob/master/pyqstrat/notebooks/building_strategies.ipynb

The discussion group is at https://groups.io/g/pyqstrat

Please let me know if you decide to use it and any feedback to improve it.

Best,

Sal

[maxim gir]

Hi Sal, 

I've been looking for long time a library that can handle options backtesting. You mentioned that your library supports options. Would it be possible to share a simple options backtest example to get me started? 

Thank you

[Sal Abbasi]

Yes please look at this example:

https://github.com/abbass2/pyqstrat/blob/master/pyqstrat/notebooks/options_trading.ipynb

Let me know if you have further questions. 

Best,

Sal

On Oct 1, 2019, at 9:42 PM, maxim gir <gir....@gmail.com> wrote:



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[maxim gir]

Great! thanks, By the way, what would be the best way to adopt options backtests from Pyqstrat  for live trading with IB ?

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[Sal Abbasi]

Apart from some analytics code that I share between backtesting and live trading, I write separate code for live trading and backtesting.  Trading code tends to be event-driven while backtesting is batch driven.  Apart from this, there are a lot of issues that are particular to trading such as trying to work orders to minimize slippage and vice versa such as the vectorized processing of large datasets in backtesting.

Best,

Sal

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