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OneMarketData Adds Strategy Backtesting Platform to OneTick Product Portfolio

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OneMarketData has introduced a strategy development and large-scale backtesting platform that is powered by the company’s OneTick data management and time series analytics solution and supported by global multi-asset class market history available through the OneTick Cloud. The platform is called OneTick Strategy Backtesting and is available immediately as either a hosted service or deployed software.

The backtesting platform can be combined with basic historical data access and tools for the construction of custom strategy analytics, simulated order flow and profit and loss statistics. Users have the option to subscribe to more than 150 markets offering more than 10 years of history, along with reference data, corporate actions, earnings and event dates.

OneMarketData built OneTick Strategy Backtesting to address the need for large-scale backtesting. While OneTick is a scalable tick database and analytics platform, it left customers building their own backtesting, usually as a set of services to test trading models.

Louis Lovas, director of solutions at OneMarketData, explains: “OneTick’s Strategy Backtesting is built for systematic traders creating and deploying quant models that use intra-day alpha seeking or execution logos. It is a comprehensive solution that builds on the OneTick database and analytics and OneTick Cloud market history to deliver simulated order flows, exchange and matching engine simulation, profit and loss statistics, and optimisation. From a technical perspective, it leverages the enhanced computational environment offered by cloud and hosted platforms that have the ability to support elastic computation. This allows applications to scale up using additional servers and processor cores as computations get more demanding.”

OneMarketData expects the strategy backtesting platform to gain favour among both existing and new customers, and plans to extend its integration of OneTick with the Hadoop MapReduce computational model used to perform distributed computations across large volumes of tick data to include the platform.

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