About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

QuantHouse Offers Historical Data on-Demand to Algo Traders

Subscribe to our newsletter

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.”

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: From Data to Alpha: AI Strategies for Taming Unstructured Data

Date: 16 April 2026 Time: 9:00am ET / 2:00pm London / 3:00pm CET Duration: 50 minutes Unstructured data and text now accounts for the majority of information flowing through financial markets organisations, spanning research content, corporate disclosures, communications, alternative data, and internal documents. While AI has created new opportunities to extract signals, many firms are...

BLOG

ipushpull and Koch Automate OTC Gas Trade Booking with Gen AI Agent

Data platform ipushpull has partnered with Koch Energy Services to launch an LLM-enabled agent designed to automate the entire lifecycle of physical natural gas trades, from chat to booking. The move tackles the long-standing challenge of manual, error-prone workflows in over-the-counter (OTC) markets and signals a major step forward in the application of Generative AI...

EVENT

AI in Capital Markets Summit London

Now in its 3rd year, the AI in Capital Markets Summit returns with a focus on the practicalities of onboarding AI enterprise wide for business value creation. Whilst AI offers huge potential to revolutionise capital markets operations many are struggling to move beyond pilot phase to generate substantial value from AI.

GUIDE

GDPR Handbook

The May 25, 2018 compliance deadline of General Data Protection Regulation (GDPR) is approaching fast, requiring financial institutions to understand what personal data they hold, why they process it, and whether it is shared with other organisations. In line with individuals’ rights under the regulation, they must also provide access to individuals’ personal data and...