The leading knowledge platform for the financial technology industry
The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

QuantHouse Offers Historical Data on-Demand to Algo Traders

QuantHouse has released Historical Data on-Demand, a service designed to speed up the research, development and back-testing phase of any trading strategy, and allow clients to implement new trading ideas within days rather than weeks or months.

The company is offering up to 10 years of historical data on-demand for the US, European and Asia-Pacific markets. Access to the data is available via a web portal, so clients can search for the data they need and purchase it online using a web browser of choice. The historical datasets purchased are delivered as flat files and are 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 being refined and adjusted to optimise trading performance.

While the time taken to fulfil the research, development and back-testing cycle of a trade can push execution beyond optimal timings, QuantHouse says giving research and development teams Historical Data on-Demand will enable them to rapidly test new and current trading strategies, and detect potential losses or degradation of the strategies within days, not weeks.

Stephane Leroy, chief revenue officer and co-founder of QuantHouse, explains: “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. 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 Historical Data on-Demand service gives clients an advantage by moving them into a much more real-time environment.”

Related content

WEBINAR

Upcoming Webinar: Integrating Intelligent Machine Readable News

Date: 30 November 2021 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Intelligent machine readable news is a powerful tool in the arsenals of trading and investment firms seeking competitive advantage. It turns unstructured data into actionable insight and can be used, for example, to uncover market trends, identify correlations and...

BLOG

UOB Deploys Chronicle EFX for Electronic FX Pricing and Trading

Asian bank United Overseas Bank (UOB) has deployed Chronicle Software’s EFX solution in Singapore to power its FX pricing and trading engine. By deploying EFX and taking advantage of reduced latency via colocation connectivity, UOB aims to improve price discovery to provide customers in the ASEAN region and across its global network with access to...

EVENT

TradingTech Summit Virtual

TradingTech Summit (TTS) Virtual will look at how trading technology operations can capitalise on recent disruption and leverage technology to find efficiencies in the new normal environment. The crisis has highlighted that the future is digital and cloud based, and the ability to innovate faster and at scale has become critical. As we move into recovery and ‘business as usual’, what changes and technology innovations should the industry adopt to simplify operations and to support speed, agility and flexibility in trading operations.

GUIDE

Trading Regulations Handbook 2021

In these unprecedented times, a carefully crafted trading infrastructure is crucial for capital markets participants. Yet, the impact of trading regulations on infrastructure can be difficult to manage. The Trading Regulations Handbook 2021 can help. It provides all the essentials you need to know about regulations impacting trading operations, data and technology. A-Team Group’s Trading...