Tick data (deep, granular time series of market prices and transactions) is the lifeblood of trading in liquid markets. Some consider it "big data," while others consider it business as usual. But all consider it essential.
Tick data is used for a wide range of purposes, from developing and backtesting trading strategies, to assessing execution quality and measuring risk. Recent trends like the growth and sophistication of automated trading and the proliferation of new regulations place a premium on technology that can accelerate the analysis of tick data or broaden its use at a lower cost. Trading organizations need to understand the potential of new technologies to help, whether those relate to storage (including non-volatile RAM, parallel file systems, and advanced storage architectures), servers, or tick-database software. Such technologies are hot topics at STAC Summits.
Tick data solutions tend to fall into two categories:
- Enterprise tick data warehouses with associated analytic engines. These serve a wide range of use cases across a trading organization. A few years ago, a number of banks and hedge funds gathered to develop the STAC-M3 Benchmark specifications based on a representative set of workloads. STAC-M3 has a suite that establishes baseline performance metrics for any technology stack, as well as an optional suite that scales up to large volumes and numbers of users, and a suite that provides realistic performance results for relatively small datasets.
- Backtesting environments. Developing trading strategies and testing them on out-of-sample data is a discipline all its own. And whether those strategies are alpha-seeking or aimed at achieving best execution for customers, the workload just gets more challenging, thanks to increasingly sophisticated competition and mounting data volumes. In 2013, the STAC Backtesting SIG formed to establish benchmark standards for technology with potential to help these workloads. (In fact, it spun out of the first meeting of the STAC Big Data SIG.) The SIG has agreed an initial draft of benchmark specifications and is now developing the software and metadata required to run them.