Elsen helps world-class financial organizations build solutions that help them or their clients overcome their most difficult data problems.
Elsen partnered with Thomson Reuters to offer its hedge fund and investment management clients the functionality they needed to effortlessly harness and use tremendous amounts of time-series data to test investment strategies.
The application developed – QA Point Powered by Elsen – is intuitive and easy-to-use, leading to an average outcome of 35X time savings on a typical user workflow, based on an industry norm.
To test a client’s high-performance computing requirements for a generic bond portfolio, Elsen developed an application on the Elsen nPlatform that calculated the portfolio value for 100,000 bonds with equal portfolio weights. Each bond had its own Floating Spread, Coupon Payment Frequency and Time to Maturity.
The application also calculated 1 million reference and discount rate curves, where the curves were defined as Base rate + an Adjustment, where the Adjustments were provided by client (in production, these are generated through a Monte Carlo process).
Average time to process 1 curve: 14 ms
Total time to process 1M curves: 3.6 hours
Rather than running volume-weighted average price (VWAP) computations over nights and weekends to populate the in-memory database for quick retrieval throughout the week, an investment firm wanted to be able to compute VWAP calculations at any time to eliminate the need to store pre-computed values.
Elsen developed an application on the Elsen nPlatform that retrieved aggregated data for a given security between two set timestamps. For example, the application should be able to compute the total volume and VWAP price for ticker IBM between 9:30:45.1000 AM and 11:45:15.3000 AM.
The client’s request: “If we make 50,000 calls for such data, we want to implement a process where each core on a GPU would compute this linear algebra in a parallel fashion.”