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experienced prop trader details his custom Python algo trading setup
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Created: by Jack Larkin Attachments:0

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experienced prop trader details his custom Python algo trading setup

  #1 (permalink)
Toronto Ontario
 
 
Posts: 25 since Jan 2013
Thanks: 3 given, 38 received

experienced prop trader details his custom Python algo trading setup

From: https://fxgears.com/index.php?threads/python-development-environment-jacks-technology-stack.1090/

Snippets:


Quoting 
My primary language is Python. Despite some uninformed beliefs that Python is too slow for algo trading, and that algorithmic trading is best left to C/C++ or some hardware programmed FPGAs, Python is perfectly suitable and more than fast enough for any retail trader who wants to get into algorithmic trading.


Quoting 
Despite what some believe, you don't need very beefy hardware to trade or algo trade. A few of my best and most profitable trades have been done on an old netbook with a 10", low resolution, screen. People who invest into expensive hardware, computer setups, etc.. before they even have a prof of concept hammered out (be it a trade plan, or algo strategy,) are putting the 'cart before the horse.'


Quoting 
Algos are good for when you don’t have enough hands, eyes, or aren’t fast enough to do something manually. If you already can do something efficiently on your own, then turning it into an algo will only make performance worse because I can’t encapsulate your years of experience into lines of code. Also, if you ask me to code up a moving average crossover strategy, we aren’t friends anymore.

Everything is tied together with Python, ZeroMQ, and open source libraries. Even uses free data feeds like IEX.

Thoughts? Anyone else take the same approach?


Last edited by Jack Larkin; April 19th, 2019 at 06:10 PM.
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  #2 (permalink)
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  #3 (permalink)
Legendary Market Wizard
Houston, TX
 
Trading Experience: Advanced
Platform: XTrader
Broker/Data: Advantage Futures
Favorite Futures: Energy
 
Posts: 2,962 since Dec 2013
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Just FYI I think the first and second quote are comparing Algo trading to HFT which I think is a silly comparison. Comparing Python to Tradestation or Ninja would be more appropriate. The latter don't require C++, co-location or expensive hardware.

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  #4 (permalink)
south africa
 
 
Posts: 170 since Dec 2018

"then turning it into an algo will only make performance worse because I can’t encapsulate your years of experience into lines of code."

What an utter crock of shit. Why don't we just say "I can't put this into code because I am using magic. My systems get worse when I don't use magic".

The whole reason to put something into an algorithm is because people are fantastic at doing dumb and random things when faced with the type of choices presented in a trading situation.

Encapsulating exactly what you are doing is never going to make things worse.

Python being too slow is something from like 2005.

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  #5 (permalink)
Philadelphia, PA
 
Trading Experience: Intermediate
Platform: Matlab, TradeStation
Favorite Futures: Stocks
 
GoldenRatio's Avatar
 
Posts: 197 since Aug 2012
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IEX data has lots of errors.

Historic O,H,L,C values can sometimes be off significantly.

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  #6 (permalink)
Toronto Ontario
 
 
Posts: 25 since Jan 2013
Thanks: 3 given, 38 received


GoldenRatio View Post
IEX data has lots of errors.

Historic O,H,L,C values can sometimes be off significantly.

That's because it's only IEX data, not SIP data.

That said, I use IEX for their earnings calendar, news, stock metrics, and other feeds.. contextual stuff for stocks, not for price / quote data.

People who use IEX's API for quote data are caught up on the "free" aspect of it and not going to get far.

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  #7 (permalink)
south africa
 
 
Posts: 170 since Dec 2018

Free data has errors because no one has been paid to clean it.

I was watching a video on astronomical data analysis yesterday and the dataset was 60 terabytes. Of course the first thing you have to do is figure out what kind of errors are in the data set. That is a non trivial problem with 60 terabytes.

With the datasets we are talking about this is a trivial problem to solve. The datasets are small and you can just replace the errors with an average value or previous value.

Even on daily data, if replacing some bad days with an average value or previous day value ruins everything there is not a chance that system is working out of sample.

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