Thanks for pointing to the paper, haven't read it yet.

But it sounds pretty interesting, especially if you correlate it with things like insider's tradings (both buy and sell) and of course whatever external events there may be.

Talking of quant, would you mind sharing what is your typical stack, especially non-proprietary, non-confidential, stuff such as languages and libraries.

I don't do anything low latency so its mostly the common scientific python stack -- numpy, pandas, sklearn, etc. Mostly linux, lots of Spark, some R and C#. We're really flexible on what we can use to solve our problems but the team has pretty much settled on python as both developers and analysts can work together more easily.