Lots o' Ticks:Realtime high performance time series queries on billions of trades and quotes

Financial mathematicians think they can predict the future by looking at time series of trades and quotes (called ticks) from the past. The main evidence for this hypothesis is that prices uctuate only by a small amount in a given day and more or less obey the mathematics of a random walk. The hypothesis allows traders to price options and to speculate on stocks. This demonstration presents a query language and a parallel database (50-way parallelism) to support traders who want to analyze every tick, not just end-of-day ticks, using temporal statistical queries such as time-delayed correlations and tick trends. This is the first attempt that we know of to store and analyze hundreds of gigabytes of time series data and to query that data using a declarative time series extension to SQL (available at www.kx.com).