What knowledge is important for algo. trading or equity research?

[echostate]

For a statistics/computer science guy to find a junior position in 1) algo. trading or 2) quantitative equity research (yes, I know they are two different positions, but both of them need statistics and programming to analyze large-scale data set), what knowledge/skills are important (in addition to econometrics/time series/market microstructure)? Any good book or resource to recommend?

Thanks.

 

[DominiConnor]

Signal processing is also useful.
This is a domain where even if you work in some other language like C#, Java or Slang, they look down their noses at you if you don't have C++ skills.

Doesn't hurt to know about Kelly criteria.

Currently the only directly useful work on the subject I know of is part of the CQF, and even that is only an introduction.

But this is a currently sexy area, and there are books coming. Part of my homework is to revue a promising book to be published by Wiley.

An interesting introduction to the game is Khaqndanis & Lo's paper on how some algotrading went wrong last summer.
http:/papers.ssrn.com/sol3/papers.cfm?abstract_id=1015987

It doesn't hurt to learn FIX, but that's tricky to acquire except though work.

 

[echostate]

Many thanks for the information!

Hope the book you mentioned will be published soon. I can find a few recent books on portfolio management/optimization, but none of them received positive rating consistently at amazon. For books in algo. trading, things become even worse.