Financial Data Management
Improve efficiency and reduce costs with the Algorithmica History Server.
Enterprise data management
The Algorithmica History Server (AHS) is a scalable data management platform designed for the financial industry. It streamlines the sourcing, cleaning, and distribution of validated data to applications. AHS addresses the rising regulatory demands, data quality challenges, and integration complexities, while reducing operational costs.
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Create your Golden Copy
AHS offers a scalable platform for sourcing market, instrument, reference, index, and corporate action data. It integrates multi-vendor feeds, both streaming and file-based, with automated quality control and master record creation.
AHS centralises and standardises your market and reference data, enabling the creation of a reliable golden copy — all stored and maintained in one consistent source.
By consolidating your data management with AHS, you gain immediate cost savings and improved data quality.
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Control of data utilization and cost
Modern financial data comes at an increasing cost. The AHS will streamline and optimise data purchases across vendors, including market data, instrument definitions, corporate actions, and index constituents. This reduces costs and improve efficiency.
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Coherent and quality assured data
The AHS ensures transparent, controlled, and configurable data processing, enabling automated validation, cleaning, and enrichment for consistent, quality-assured data across downstream systems.
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Large number of supported feeds
The AHS uses standard off-the-shelf feed loaders, upgrading them in sync with your vendor while ensuring compatibility with old feed standards. Simply subscribe to updates — we handle the rest.
Advanced calculation capabilities
AHS includes advanced calculation capabilities along with the full Quantlab financial code library and development environment.
With this powerful support, clients can define internal yield curve formats, volatility surfaces, commodity forward curves, and other custom-derived data.
By consolidating all your data management needs within AHS, you gain immediate cost savings and improved data quality.
With over 20 years of around-the-clock experience managing feeds like Bloomberg B-pipe, Server-API, Data Licence, Reuters Triarch, RMDS, Eikon, Datascope, we ensure reliable, fault-free market data capture.
Quantlab Batch Server
With the Quantlab development environment and built-in calculation methods, you can easily create derived data in your internal data store. Scheduling and monitoring are managed via a web console, accessible from multiple locations.
Volatility surfaces
A long standing problem for many financial institutions has been obtaining fair market values for older option trades. We have solved this by creating fair volatility surfaces using the current liquid market quotes and from these pricing any positions that do not have IFRS compliant liquid pricing.
Yield curves
An even more common problem among many institutions is finding yield curves calculated to fit into legacy systems. Having models such as those required by the EIOPA to discount liabilities, it is easy to create inhouse solvency II compliant curves using swap market yields as the only input.