SciComp's skilled quantitative development team provides expert, cost-effective consulting services associated with asset and risk management simulation models.
With over 50 years of cumulative experience, SciComp's team of numerical experts has worked closely with top tier practitioners around the globe implementing derivatives pricing and asset and risk management solutions at major financial institutions.
Asset and Risk Simulation Model Design and Review
SciComp's asset and risk simulation model expertise includes the design, implementation, enhancement and testing of asset and risk simulation models and their components. Employing a sophisticated suite of numerical routines and methodologies SciComp provides robust and highly performant asset and risk simulation models.
Sample projects include:
Asset Simulation Model
Simulation model projects risk factors and returns for a broad range of asset classes over a user-defined horizon.
- Key components of the model include:
- Simulation of Risk Factors and Returns
- Model Calibration
- Utility Measurements
PCA-Based Analysis and Simulation of Risk Factors
Identification, analysis and simulation of key risk factors via PCA (principal component analysis) for asset classes including interest rates, oil and gas, and agricultural commodities including cross commodity correlations and seasonality. Customer-defined Monte Carlo based risk simulation models where included as part of the project deliverables.
Incorporating Risk Factors into Pricing Models
Counterparty and funding costs implemented into pricing models as non-linear PDEs. Funding rates may be different for lending and borrowing and the M-t-M value at default can be specified exogenously.
GPU-enabled potential future exposure (PFE) prototype.
GPU-Enabled Simulation Models
As one of the earliest adaptors of NVIDIA's GPU technology for use in financial services, SciComp has many years of experience and a high degree of expertise in GPU-enabling derivative pricing and risk solutions. SciComp’s expert GPU team will perform a thorough review of an asset/risk simulation model's design and implementation to identify and port those components best suited for GPU-enablement.