Database Reference
In-Depth Information
time scale. During any single second of trading, these programs can engage each other in an
elaborate back-and-forth game of bluff and call as they make bids and offers.
Some such trades are triggered by changes in trading volumes over recent time intervals.
Forms of program trading represent a sizable percentage of the total volume of modern ex-
changes. Computer-driven high-frequency trading is estimated to account for over 50% of all
trades.
The velocity of trades and therefore the collection of trading data and the need in many cases
for extremely small latency make the use of very high-performing time series databases ex-
tremely important. The time ranges of interest are extending in both directions. In addition to
the very short time-range queries, long-term histories for time series data are needed, espe-
cially to discover complex trends or test strategies.
Figure 2-2
shows the volume in millions
of trades over a range of several years of activity at the NYSE and clearly reveals the unusual
spike in volume during the financial crisis of late 2008 and 2009.
