pysystemtrade

There are already many python packages where you can back test trading strategies. Some of them also include a framework for automatic execution and complete position management.

I can't give an exhaustive list but I'll pick out:

- Quantopian's  zipline
- BT
- pythalesians
- pyalgotrade

There is a longer list here. 

Does the world really need another one? Well, probably not, but today I've released one anyway (this explains at least partly why it's been a month since my last post, since I've spent the last month writing it).

You can find pysystemtrade on github, here. This is version 0.0.1. It provides a basic backtesting enviroment that implements the 'staunch systems trader' example in my book. And it's GPL 3 open source.

However it's my intention that this will become a fully featured back tester that will include all the optimisation and calibration techniques that I've discussed here on the blog, and in my book. It will also, eventually, include a complete end to end system that can be used for fully automated futures trading with interactive brokers.

Why am I doing this?

Having said that this is probably a futile exercise, it's probably worth explaining why I've released this today.

My own code needs rewriting

I've been running with a trading system that I wrote in early 2014 for the best part of 21 months. Whilst it's been pretty stable, it isn't very pretty or extendable.  There are things I'd like to do with my system that I can't implement without having to do a massive refactoring; massive enough that a rewrite from the ground up would be better. Parts of it are over engineered; other parts too tightly coupled. I'd probably make different decisions about many parts of it with the experience I've had. I'd also like to move to python 3.

Oh yes pysystemtrade is in python 3; well 3.4. Didn't I mention that? Sorry...

So the job of rewriting this code has been on my back list for some time. Doing it in public will hopefully encourage me to finish the job.

I like to write my own stuff

A question I'm often asked is why I didn't write my original trading system as part of, or as an extension of, one of the libraries I mentioned above. It's equally valid to ask why I'm writing everything from scratch again.

I've worked with quite a few backtesting frameworks in my life. I've never been completely happy with frameworks that someone else has written. Whenever you use someone elses stuff there is an obvious benefit, but three costs. The first cost is the time penalty in understanding how to use the product. The second is the time spent in extending it to do what you want it to do.

Since I already know that 95% of the final code base isn't going to be back testing, but production implementation of a trading system, the benefits of using someone elses backtesting framework are mostly outweighed by these two costs.

Also as a linux user I get irritated when to use someone elses code I have to install a huge stack of python libraries first. That's why there are minimal dependencies for this.

The third cost is that you have to put up with the API that the developer has imposed. In particular I'm very choosy about how I spend my time at the command line developing systems on the fly (in my previous job I spent a lot of time moaning at technologists when they tried to create a trading system that was lovely and robust, but hard to use interactively. They got it right in the end).

Finally it's just more fun to write your own stuff; if you're a strange person like me.

By the way I know that there are many of you who also like to, and have, written your own stuff. So I'll try and keep the code relatively modular. When I drop my optimisation code into the project, it should be easy to remove it and tie it into your own system. Should you want to use a different broker, or different storage and data feeds, I'll make that as straightforward as I can.

Pro-bono publico

 
I've noticed that writing on this blog has involved writing quite a bit of code (and I keep getting requests to write some more). Whilst the original series of posts I wrote about using swigibpy is quite self contained; subsequently I seem to be putting together quite a little messy pile of code in the systematictradingexamples repo..

Rightly or wrongly I reckon it will be better for all concerned if I created a single project that held all the code I use to demonstrate techniques and points of interest. At some point I'll circle back and rewrite the examples in systematictradingexamples into this new project).

Encouraging people to trade properly is a bit of a mission of mine. If this project helps one person who would otherwise be using some overfitted 'robot' trader tied to an expensive broker, then it will be worth it (though I'd hope for a better return on my time).

Sorry - no support

I had one big concern about releasing my code open source. Not that I would give away any deep secrets; as you will know if you've been paying attention I don't believe in secret sauce.

I also have the natural embaressment of showing people my code, especially given I am not by any means a professional programmer. So be nice, or I'll pull it all from the repo :-)

No I was concerned, based on my experience with the code I've already released, that answering emails of the 'this doesn't work' type will eventually take all my time. For this reason I've decided (a) this project will be thoroughly documented and will have some tests, and (b) I won't be committing to to help you with any problems. Here's what I say in the README file:

"This is an open source project, designed for people who are already comfortable using and writing python code, are capable of installing the dependencies, and who want a head start on implementing a system of their own. I do not have the time to provide support. Of course I am very happy if you get in touch with me on any of the following topics:

• Confusing error messages
• Missing or misleading documentation
• Suggestions for extra features

However I can't guarantee that I will reply immediately, or at all. If you need that level of support then you are better off with another project.
I'll try and incorporate any feedback into the code, but this is a part time venture for me, and it will be competing with my other interests (writing books, blogging and research). But if you occasionally check github you will hopefully find it gradually improving. Offers to contribute will of course be gratefully accepted."

Look guys let me make it clear. You're getting the benefit of my distilled wisdom for free (though some of you have shelled out up to $60 for my book, for which I thank you from the bottom of my heart); something my former employer used to pay quite a lot of money for. But becoming an unpaid technical support monkey for a bunch of strangers (and a few old friends and colleague) on the internet isn't my idea of fun. I'll make an effort to release stable code, write a few tests, and document it properly, but then you're on your own.

Also this is open source. I know for a fact that at least half the people reading this blog are better programmers than I. If you find a bug or want to improve the code in some way, then please feel free to offer to do it (and thanks to those of you who have offered, or have already done so).

A very quick demo

There is a long demo, and an even longer user guide, in the repo so I don't need to repeat them here. Instead here is how you'd simulate the system in chapter 15 of my book, in three lines:


from systems.provided.futures_chapter15.basesystem import futures_system
from matplotlib.pyplot import show

system = futures_system()
system.accounts.portfolio().sharpe()
system.accounts.portfolio().curve().plot()
show()

The account curve for the system in chapter 15 of my book. Sharpe Ratio 0.48

Seasons greetings to one and all

This will be my last post for the year. I hit a high water mark in my trading account yesterday so I'm in a good mood. So please feel free to enjoy the warm feelings I am currently transmitting into this keyboard, have a good holiday, and see you next year.