An Algorithmic Trading Framework

I’m dreaming here. But if I were to build the ultimate framework for algorithmic trading, what would it look like?


One purpose would be to concentrate more on the algorithm, and less on the mechanics that all strategies need. But this is tricky. All strategies need something different, with different parameters.

Another purpose would be to have a consistent way to write complete algorithms. Once the framework is learned, adding new and updating old ones become easier.


There are a myriad of options for implementing trading algorithms. A simple idea can quickly turn into a long list of questions.

Risk measures must be looked at. How is the optimum trade size calculated? Are other instruments involved in this calculation (i.e. Would this trade create a risk in a particular index or industry that is above an allowed threshold?).

We must consider order entry. Will it be a market order? Do we attempt to make the spread? Which ECN will be used? What do we do if the order is not immediately filled? What if the order is partially filled?

Then there is order management. At what point is the trade closed at a loss? Is there a strategy for adjusting risk if the trade moves for/against the entry price? How are profits taken?

There is also brokerage and data feed questions. Are these decisions already made? Is there the possibility they will be changed in the future?

With such questions answered (or at least partially answered), we begin to look at frameworks that can help build the infrastructure.

If we’re sticking to a particular broker or software package, the framework decision becomes easy. If we’re talking FOREX, and the broker mainly works with Metatrader, there would need to be a strong reason to choose another platform.

A trading business must also look at in-house experience that is available. A hedge fund that has a staff of Python developers may not want to work with a C++ framework.


A “one size fits all” trading platform will never be created. A platform that works well for a particular situation is often available. I would like to build a platform that is somewhere in the middle of those two situations. I would like to hide the complexities of portfolio management, broker connectivity and data feed connectivity by providing a (somewhat) generic interface to these items.

Strategies that connect through an API to these resources would be somewhat more portable between brokerages, data providers, and changes to portfolio management rules. This would also hopefully allow for backtesting without rewriting.

A while back, I started down the road of building such a framework. A rough implementation is at GitHub. And by rough I mean pre-pre-alpha. There are plenty of areas that need work, or even redone. But it is a start.

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