Index of /transputer/finengineer
Crazy collection of financial PDF's
Huge list of articles on finance-related topicsa bestiary of algorithmic trading strategies « Locklin on science
Quants come in three basic varieties. 1. Structurers: people who price complex financial instruments. 2. Risk managers people who manage portfolio risk 3. Quant traders people who use statistics to make money by buying and selling most quants are structurers. Of course, there is often bleed over between these varieties -but it’s a useful taxonomy for looking for work. I’ve done a little of all three at this point (very little, honestly), and have always liked quant trading problems more than the other two varieties. It’s the most ambitious, and the most likely to net you a career outside of a large organization (go me: Army of one!). It’s also the most mysterious, since successful quant traders don’t like to talk about what they do. Structurers and risk managers have to talk about what they do, almost by definition. Quant traders gain little from talking about their special sauce.
***** very good and deep articles on finance topics by "Locklin on science"
vocab of "job specs" in tradingTechnology Review: Blogs: Guest Blog: AI That Picks Stocks Better Than the Pros
From MIT. Information on Emerging Technologies & impact on business & society
academic study claims to use text in news to automate trading and beat Wall Street. Tested on 5 weeks + bizarre informative features --> sounds fishy
The ability to predict the stock market is, as any Wall Street quantitative trader (or quant) will tell you, a license to print money. So it should be of no small interest to anyone who likes money that a new system that works in a radically different way than previous automated trading schemes appears to be able to beat Wall Street's best quantitative mutual funds at their own game.
It's called the Arizona Financial Text system, or AZFinText, and it works by ingesting large quantities of financial news stories (in initial tests, from Yahoo Finance) along with minute-by-minute stock price data, and then using the former to figure out how to predict the latter. Then it buys, or shorts, every stock it believes will move more than 1% of its current price in the next 20 minutes - and it never holds a stock for longer.