I just spent the last few hours looking into Google App Engine to use it for trading. Google App Engine (GAE) is a cloud computing development and hosting platform for web applications. GAE is similar to the well-known Amazon EC2 service but it is also very different. The main difference between GAE and EC2 is that GAE is not as flexible as EC2 but it is a lot easier to develop on. Think of it like using C++ (EC2) to write your own trading platform to using EasyLanguage on TradeStation or MQL on Metatrader (GAE). Another advantage for using Google App Engine is that it is free! Well, to a certain extent. It is free for a limited monthly usage. However, Google's free quota is known to be very generous (think Gmail) and this is no exception. Based on the numbers, it looks comparable to a typical \$20/month virtual private server (VPS) hosting package. My guess is that you can run a decent personal quant program on it if you keep the resources for yourself (private use). For more information on the free quota, you can read the current GAE quota web page or the Wikipedia page for GAE. You might be wondering how did I spend a few hours just reading on GAE? The answer is that I've done a brief research, planning, and assessment to see how GAE can be put to use in terms of quantitative analysis for automated and discretionary trading. Without going through all of my notes and logic, here's the gist of my conclusion.

For Automated Trading

Since GAE is also a SDK, it has a restricted programming API. You can't just plug in any custom library of your own (i.e. your broker's API) into your program. That is its advantage and its disadvantage. Furthermore, GAE only support HTTP and HTTPS. So you can't open a socket for your connection either. These limitations won't be changing anytime soon as GAE is designed to be like that for security reasons. Basically, there's no way for your web application on GAE to connect with your broker for trading. So much for that idea.

For Discretionary Trading

Things look brighter for discretionary trading though. A big bonus with using Google App Engine is that it supports the Google Finance API. Google Finance offers free real-time stock quotes. Combine it with the programming capability of the Google App Engine and you have yourself a free number cruncher in the cloud. However, GAE is definitely no match for your personal computer, so why would you go through all that trouble? One possible scenario in which this could be useful is for traders that is often on the road or traders such as myself in which we have a day job. In that case, you can set you quant analytics on GAE as a private web application and then you can access it as a web page anywhere on your mobile phone. One of the obvious limitation with using GAE is that it has limited features for scientific computing. For example, it doesn't support Numpy in the Python SDK. As such, I can't imagine using GAE for anything more than simple technical analysis for now. I certainly hope that GAE can include more powerful scientific computing capabilities in the near future. Until then, I really can't see Google App Engine offering much help aside from performing algorithmic tasks to help with your trading analysis. Their open issues log does announce that Numpy is being integrated into GAE though. So that's a great sign for things to come! I am very hopeful of GAE's potential as a free cloud server to host my quant analytics on. We'll just have to wait for now.