QuantHouse has announced the launch of Historical Data on-Demand designed to speed up the research, development and back-testing phase of any trading strategy.
The firm says the research, development and back-testing phase is a critical but historically lengthy and onerous process, adding that market participants must identify data sources, align formats and code to those data sources, allocate storage capacity to download the necessary files and ultimately incorporate into their trading models to assess the viability of their trading strategy. By this time the market has often moved on and the back-testing cycle needs to be repeated, it adds.
The new service is, QuantHouse claims, the first of its kind to speed up this process and delivers historical data-on-demand for use in any client model and allows clients to implement new trading ideas within days rather than weeks or even months. It offers up to 10 years of historical data for US, European and Asian-Pacific markets. Access to the data is available via a web portal, so clients simply search for the data they need and purchase it online using their web browser of choice. The historical datasets purchased are delivered through flat files and available for immediate integration into any system, without the need to integrate an API. Historical data can be replayed over prior time periods with the results then being refined and adjusted in order to optimise trading performance.
“The trading landscape has changed significantly in the past few years; it is no longer about how fast your trades are sent, but how quickly your trading strategy can be ready,” says Stephane Leroy, chief revenue officer and business co-founder, QuantHouse. “In order to move away from speed trading to smart trading, you need access to trusted, reliable and consistent data on-demand, so that you can spot changes and emerging patterns in the market quickly and evaluate and adjust your trading strategy accordingly. Our new Historical Data on-Demand service gives clients a distinctive edge by moving to a much more real-time environment. This provides a real breakthrough for the algo trading industry.”
Denery Fenouil, chief technical officer at QuantHouse, adds, “The length of the research, development and back-testing cycle often pushes the actual execution of the trade beyond optimal timings. By giving your research and development teams the right tools like Historical Data on-Demand, they will be able to rapidly test new and current trading strategies in order to detect potential losses or degradation of the strategy within days, not weeks. This then enables clients to quickly adjust their trading strategies, in order to make the changes needed before it hits your P&L.”