Financial Data Management
A Scalable Data Management Platform
The Algorithmica History Server, AHS, offers a modern, enterprise-wide data management platform, specifically built for the financial industry. It provides you with a highly scalable solution to efficiently source, clean and distribute validated data to down-stream applications.
The regulatory requirements have put an increasing challenge on financial institutions and their existing data management frameworks. New data requirements and an increased need for quality and validation has become a major challenge. In addition, new data vendors, new sources and different integration technologies add an extra layer of complexity. As a consequence, financial data has become an increasingly expensive part of day-to-day operations.
Algorithmica’s Enterprise Wide Data Management Solution, AHS, is Built With All This in Mind.
AHS provides you with a scalable platform to meet existing and future requirements when sourcing market, instrument, reference, index and corporate action data to downstream applications.
The AHS integrates multi-vendor feed handling using both streaming and file based feeds from most major vendors. It ships with automated quality control and internal creation of master records.
Advanced Calculation Capabilities
AHS comes with advanced calculation capabilities and the complete Quantlab financial code library and development environment. Using such calculation support, a client can define internal yield curve formats, volatility surfaces, commodity forward curves and other internally derived data.
By consolidating all your data management requirements to the AHS, you achieve immediate cost savings and quality improvements.
Control of Data Utilization and Cost
Modern financial data comes at an increasing cost. The AHS will economize purchases of data from multiple vendors – be it market data, instrument definitions, corporate actions or index constituents.
Coherent and Quality Assured Data
The AHS provides full transparency and control of incoming and normalized data and has unrivalled configurability to support complex automated validation, cleaning and enrichment requirements. The result: coherent and quality-assured data across all your downstream systems.
Large Number of Supported Feeds
The AHS is using standard off-the-shelf feed loaders. We upgrade the front end loaders in sync with your vendor and maintain compability with old feed standards. You only need to subscribe to updates. We do the rest.
File and Realtime Server
INTEGRATION WITH MARKET LEADING FEED SOLUTIONS MADE SIMPLE.
Creating an inhouse data store with financial data coming from multiple vendors is a simple project when using the realtime and file based front-ends for the History Server. The History Server handles price data, static data, corporate actions, and index constituents in an integrated data model, serving the end-users or systems in a unified way.
In addition, a complete scoring and validation system makes day-to-day operations easy and compliant.
For fault-free market data capture, experience is key. We have +20 years experience running 24/7 operations with feeds such as Bloomberg B-pipe, Server-API, Data Licence, Reuters Triarch, RMDS, Eikon, Datascope and many more.
Quantlab Batch Server
CODE, DEPLOY, SCHEDULE AND MONITOR ANY FINANCIAL CALCULATIONS NEEDED
Using the Quantlab development environment, or simply using some of the built-in calculation methods, you can easily create additional derived data in your internal data store. Scheduling and monitoring calculations is handled through a web console that can be supervised from multiple locations.
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.
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.