Intrigued by Vhayu's announcement of a complex event processing tool geared toward quant researchers, yesterday I looked at this software. It gives quants a means to look for patterns, test ideas and strategies and run what-if scenarios against massive volumes of real-time and historical tick data. It combines some of the features of mathematical algorithmic modeling tools (such as Numerix and Algorithmics) with a fast historical and real-time tick database (a la Vhayu, Kx) with a front-end complex event processing graphical user interface (in the vein of Progress Apama, Streambase or Coral8).Using Velocity for Quant Researchers, a quant researcher could browse through five or 20 years of tick-by-tick market data about a certain asset class. He or she could look at all futures contracts of the last five years to detect patterns around certain historical events. He could perform pre-trade analytics such as VWAP (volume weighted average price) which lets him follow the market midpoint. She could quickly generate line graphs and Bollinger bands of particular asset activity to analyze past performance and trade activity. (How many female quant researchers there are on Wall Street is an interesting question I've never tried to answer or even thought of before now.)

Velocity for Quant Researchers puts an open-source-based user interface in front of the existing Velocity tick database. It's built on the Eclipse open-source development framework and written in R, a free variation of the statistical package S+, which is popular in the quant community. "There are a lot of financial engineering students coming out of academia who are very familiar with R and have used it extensively," says John Coulter, head of business development. Vhayu also offers adaptors for S+ and Matlabs, two common languages used by quant developers. It also provides adaptors for Portware and Flextrade, so that strategies developed and tested within Velocity can be executed in those EMSs, and is collaborating with other CEP vendors to integrate their graphical user interfaces with Velocity's time-series database. Unlike the usual Velocity configuration, in which it may run across many servers, this version for quant researchers can run on a single quad-core Pentium PC. Vhayu will soon post the program on vhayu.org so that users will be able to share analytic libraries with one another.