Caml Trading

People who are nervous about hiring people in a relatively unpopular language should watch this video[1] at the 1:01.00 mark by Yaron Minsky. [1] ▶ this video

That's just not true. There are whole companies based on algorithmic trading. Jane Street, for instance, has a tech talk on how they take advantage of Caml in automated trading. ▶ this video

You most certainly can, just not with such naïve approach. Jane Street is a company that does it, and they are quite open about their tech approach (just not about their specific models): ▶ this video Jane Street went from zero to trading $1 trillion in volume in just 15 years.

Jane Street is one of the few companies which are betting heavily on OCaml, it makes sense to go all functional in the high frequency trading world I guess. It's purportedly been C/C++ for most of that industry, probably not the best toolset for keeping error rates low in a complex environment. Fascinating to read how far beyond language decisions they need to think to shield themselves against outages (and competitors?). I did a little bit of experimentation with OCaml by playing with bitcoin exchange APIs during the China boom some months ago, but I unfortunately didn't push further to a point where I'd be using Jane Street's open source libraries. It still was very interesting and IMHO totally worth it if not just for the functional programming practice. Relevant video on how OCaml gets used at Jane Street: ▶ this video

Jane Street Capital uses OCaml for their trading system. Yaron Minsky explained that one of the main benefits of it was that people could read and understand the code much better than the other languages they tried (including C#). Yaron's talk: ▶ this video

> We (I work for Quantopian) will surely support other order types when we support live trading. I suspect they won't be true limit orders, but stop orders (true limit orders wouldn't slip). Also, for a passive trading algorithm its important to have level II data (the order book), or the algorithm is flying blind. Re 1, its not the size of the data set which prevents overfitting (larger data sets actually make it more likely), but the use of it when developing/training the algorithm. Repeated testing and tweaking the algorithm will overfit, unless one is careful to maintain the complexity of the algorithm. Anyway, best of luck to your users! But they should be warned that active trading on signals (price prediction) is the hard way to algorithmic profit. That's why market making and arbitrage is the bread and butter of the pros, not signal trading.[1] 1. said as much here somewhere in the first 20:00 ▶ this video