QuantHouse to provide TSL machine learning capabilities as part of the QuantFactory cloud backtesting suite
Offering full-automation and efficiencies for the design, testing, and code-writing of trading strategies
London, Paris, Chicago, Sydney, 30 June 2020: QuantHouse, the global provider of end-to-end systematic trading solutions including innovative market data services, algo trading platform and infrastructure products and part of Iress (IRE.ASX), today announced that Trading System Lab® (TSL) has added their machine learning capabilities as part of the QuantFactory cloud backtesting suite.
The QuantFactory cloud backtesting suite provides a fully configurable environment in which clients can develop, backtest, optimise and implement quantitative trading strategies that can later be executed in a standalone, live-trading environment. Machine learning outputs from TSL are integrated into the QuantDeveloper module of QuantFactory.
Machine learning delivers a number of advantages to clients which includes increasing the scope of trading strategies available, increasing the number of markets an individual can monitor and respond to and, incorporating a wider range of data sources.
TSL provides machine learning capabilities that automate the design and development of trading strategies. This enables TSL to deliver far more innovative strategies, design thousands of strategies per second and per instance, reduces time to market and is interoperable with all data, markets, frequency and programming languages.
Salloum Abousaleh, Managing Director - Americas, QuantHouse, said, “Machine learning increases the scope of trading strategies available and the number of markets and data sources that an individual can process and respond to. QuantFactory and TSL combined, drastically reduce the time to engineer and deploy algorithmic trading strategies and automatize what is often a tedious manual process. This collaboration is part of our ongoing commitment to simplify access to quantitative trading that enables our clients to reduce cost, improve quality, decrease time to market and expand their universe of novel strategies through Machine Learning.”
Mike Barna, CEO, Trading System Lab, added, “We are delighted to deliver our machine learning capabilities to the global QuantHouse community. Our integration with QuantFactory allows QuantHouse clients to rapidly deploy new strategies without writing a single line of code, while leveraging QuantHouse’s leading research and backtesting environment helps optimize and deploy the trading models generated by our platform.”
QuantHouse provides end-to-end systematic trading solutions. This includes ultra low latency market data technologies with QuantFEED, algo-trading development framework with QuantFACTORY and proximity hosting and order routing services with QuantLINK. We help hedge funds, market makers, investment banks, brokers and trading venues achieve optimal trading performance, develop and integrate new trading strategies, comply with regulatory requirements, test existing and new trading infrastructure tools and rationalize operating costs.
The “QuantHouse API Ecosystem” is a unique global initiative with the objective to provide the framework within which capital markets participants can quickly and easily gain access to multiple trading venues, technologies or applications through standard APIs. The QuantHouse API Ecosystem has developed over time to what is now the largest API ecosystem community of buy- and sell-side participants, exchanges, prime brokers, trading venues, hedge funds, market makers and other financial services partners and vendors.
QuantHouse is part of Iress (IRE.ASX), a technology company providing software to the financial services industry. Iress’ software is used by more than 9,000 businesses and 500,000 users globally. More information is available on www.iress.com.
About Trading System Lab
Trading System Lab was formed to fill the need for improved design techniques of mechanical Trading Strategies using Machine Learning. TSL’s belief is that Machine Learning based automatic design will continue to drive strategy development moving forward. The recent stock and credit market meltdowns have shown, once again, that traditional long-only money management suffers severe downside risk, forcing the discovery of novel Trading Strategies. This continues to drive an ongoing, determined effort by TSL to enhance the performance metrics of Trading Strategies for High Frequency and longer-term trading. As evident by the high attrition rate of Hedge Funds, clearly there is a need for tooling that supports the strategy designer.
With over 15 years of experience in the development, design and deployment of Machine Learning based Trading Strategies, TSL is well positioned to provide the strategy designer with powerful ML design tooling. TSL’s effort has produced the first high speed “smart designer” algorithm that provides for the automated, rapid design of financial Trading Models. Using DAS™ strategy designers can adjust strategy design criteria “during ML design” a substantial capability unique in this space. Use of this technology has initiated a paradigm shift with TSL’s machine designs outpacing human designs in independent testing.