Annotated Useful Version of Big Data Talks:
Fast Markets, "New News" & Event Trading
The first purpose of this post is to be able to provide something useful to people who have requested slides from talks I've given on structured and unstructured flavors of Big Data in Finance. The slide files themselves were huge due to all the pictures and movies. Plus, the pictures alone didn't really tell the story, and were often used just for a few seconds.
To make something useful, I went back through the slides, and annotated them with comments based on what was said, removing some and adding others with more detail than could be included in the original talks. Download the newly slimmed down 9M version here.*
“Big Data in Financial Markets” is an overly broad topic by a factor of two because markets have two big data revolutions underway at the same time.
The first revolution is related to structured market data, issues around the flash crash, unstable trading systems, and cyber security of markets. That is the subject of the first portion of this talk.
The other big data revolution in markets is in the usual sense used in the tech press – weakly structured information from textual, web, images, social media, governments and commercial sources.
A common theme in both parts of the talk is how humans can play well with machines. Future skills for "algo jockeys" and "collaborative intelligence amplified research/traders" will emphasize where people can add value to the algorithms and machinery.
The MUST SEE Kevin Slavin video on Algorithms
The other reason for this post is a bonus, to point out this extraodinary TED talk by Kevin Slavin. It does for algos what "Star Wars" did for metal swimwear. It has a broad perpesctive and almost all the examples are financial.
* Nerd Note: How to make annotated talk files:
Getting the comments to print alongside the slides was something of a challenge. From a Mac, you need to move the slides to Windows powerpoint (I used an old XP era version) and did "send to word with notes", which the Mac ppt won't do. That grows to a 400 meg file, that can be whipped down to 9M using Acrobat pro.