- Sponsor:
- sighpc
No abstract available.
Proceeding Downloads
STAC-A2™ benchmark on POWER8
The STAC-A2™ benchmark is an emerging standard designed to evaluate the speed, scalability and quality of computational platforms for performing financial risk analytics in the capital markets industry. The problem posed by the benchmark is the ...
Parallelism-centric optimization and performance study of a finance aggregation engine on modern NUMA systems
Mark-to-future aggregation is a key component of counterparty credit risk analysis in the IBM Algorithmics software. Its computation exhibits complex memory access and control flow patterns, and is hard to accelerate. The prior effort to improve ...
Optimization strategies for portable code for Monte Carlo-based value-at-risk systems
Value-at-risk (VaR) computations are one important basic element of risk analysis and management applications. On the one hand, risk management systems need to be flexible and maintainable, but on the other hand they require a very high computational ...
Potential future exposure, modelling and accelerating on GPU and FPGA
Counterparty Credit Risk is of top concern among financial institutions, as the over-the-counter derivative market has been growing rapidly for the last two decades. Potential Future Exposure (PFE) provides assessment of the safety of a bank's asset ...
Fulfilling solvency II regulations using high performance computing
Throughout Europe, Solvency II Regulations are changing the way in which companies involved in the provision of financial services must assess their solvency. Historically, solvency has been assessed using a single 'best estimate' set of assumptions. ...
Implementing deep neural networks for financial market prediction on the Intel Xeon Phi
Deep neural networks (DNNs) are powerful types of artificial neural networks (ANNs) that use several hidden layers. They have recently gained considerable attention in the speech transcription and image recognition community (Krizhevsky et al., 2012) ...
Solving the optimal trading trajectory problem using a quantum annealer
We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a formulation of the problem, discuss several possible integer encoding schemes, and present numerical examples that show high success rates. The ...
GPU option pricing
In this paper, we explore the possible approaches to harness extra computing power from commodity hardware to speedup pricing calculation of individual options. Specifically, we leverage two parallel computing platforms: Open Computing Language (OpenCL) ...
Index Terms
- Proceedings of the 8th Workshop on High Performance Computational Finance
Recommendations
Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
WHPCF '15 | 10 | 8 | 80% |
Overall | 10 | 8 | 80% |