Market Data Management

Increasingly complex quantitative strategies and the explosive growth of market data volumes are driving the need for integrating real-time analysis of market data, with historical data storage. Both buy- and sell-side firms need tools to rapidly develop algorithmic and quantitative trading strategies which run queries against both real-time market data and large historical data repositories. Firms also need the ability to easily back-test trading strategy algorithms using virtual feeds of historical data and to be able to quickly deploy trading strategies and evolve those strategies as market conditions change.

The StreamBase Event Processing Platform offers customers the ability to rapidly build algorithmic and quantitative strategies, easily back-test these algorithms against large amounts of historical data, and quickly deploy and evolve these trading strategies as market conditions change.

Rapidly Develop Trading Strategies

The StreamBase Event Processing Platform™ allows firms to develop complex trading strategies in a percentage of the time it takes using custom development techniques. In an industry where time-to-market is a key competitive advantage, this is a critical component of any successful trading infrastructure.

Back-Testing

Trading strategies developed using StreamBase can be back-tested at very low latencies using historical market data supplied by leading tick store providers. Raw and aggregated market data captured by the tick store is fed into StreamBase as a way to identify and verify the most effective trading strategies from a historical perspective.

Easily Deploy Trading Strategies

Once successful trading strategies have been identified through back-testing, these strategies can then be rapidly deployed in the live market using StreamBase. Once implemented in StreamBase, trading strategies can be changed on the fly to react to real-time market conditions. As trades are being made, StreamBase can store results and keep a record of how your algorithms perform over time for benchmarking