What are the main use cases for MatLogica AADC?

MatLogica AADC has three main application areas: (1) Finance and Insurance - XVA risk calculations, Monte Carlo simulations, derivatives pricing, FRTB compliance, model calibration, achieving 6-100x speedups and up to 99% cost reduction; (2) Machine Learning - Model calibration, custom layers, real-time recalibration, demonstrated 6x faster than TensorFlow for geophysics; (3) Industrial Mathematics - PDE solutions on large grids, automatic Jacobian calculation, geophysics, weather forecasting, fluid dynamics optimization.

How does MatLogica help with XVA calculations?

MatLogica AADC has been tested for large-scale XVA applications including close to real-time full portfolio simulations for CVA, DVA, and FVA pricing and risk calculations under FRTB regulations. The technology delivers 6-100x speedups through automatic vectorization (8-16 samples per CPU cycle) and automatic adjoint differentiation for sensitivity calculations, enabling transformation from overnight batch processing to real-time intraday risk management.

Can MatLogica AADC be used for machine learning?

Yes, MatLogica provides TensorFlow-like functionality for C++ with seamless interleaving of ML objects with business analytics. Performance has been demonstrated 6x better than TensorFlow for geophysics applications. Use cases include Monte Carlo based model calibration, real-time recalibration using tick-level data, and efficient differentiation through custom function definitions and layers.

What Monte Carlo methods does MatLogica support?

MatLogica supports a wide range of Monte Carlo techniques including American Monte Carlo for early exercise derivatives, path-wise Monte Carlo for sensitivity calculations, Monte Carlo based model calibration, and general Monte Carlo simulations for derivatives pricing with 6-100x acceleration. The vectorization automatically executes 8-16 samples per CPU cycle depending on AVX2/AVX512 support.

How does MatLogica support sustainable computing?

MatLogica AADC reduces carbon footprint through multiple mechanisms: up to 99% reduction in cloud/electricity costs by optimizing computational efficiency, extended hardware lifetime by maximizing existing infrastructure, simplified software architecture reducing complexity overhead, and 6-100x speedups meaning dramatically less computing time and energy consumption for the same calculations. This aligns with corporate sustainability agendas and green computing initiatives.

Can MatLogica kernels be executed in the cloud?

Yes, MatLogica kernels can be executed in the cloud for scalability while keeping proprietary quantitative models and sensitive market data secure on-premises. The kernels are serialized and can be deployed to cloud infrastructure, enabling organizations to benefit from cloud elasticity without exposing intellectual property or confidential data.

MatLogica AADC Use Cases and Applications

Finance, Insurance, Machine Learning, Industrial Mathematics, Scientific Computing

MatLogica AADC delivers 6-100x speedups across multiple industries through patented Code Generation AAD™ technology. Primary applications span three domains with proven results. Finance and Insurance: XVA pricing and risk calculations (CVA, DVA, FVA) achieving FRTB compliance with real-time full portfolio simulations, Monte Carlo simulations for derivatives pricing with 6-100x acceleration, stress testing and back-testing, historical VaR calculations, complex non-linear calculations including volatility interpolation and curve construction, model calibration using Monte Carlo methods avoiding inflexible analytical approximations, domain-specific language compilation for runtime flexibility with native performance. Enables processing batches in real-time, reduces cloud/electricity costs by up to 99%, simplifies software architecture, and extends hardware lifetime. Vectorization executes 8-16 samples per CPU cycle automatically. Machine Learning: Provides TensorFlow-like functionality for C++ with demonstrated 6x better performance than TensorFlow for geophysics applications. Enables Monte Carlo based calibration of complex multi-asset models, real-time model recalibration using tick-level data for accurate up-to-date information, custom layer creation with efficient differentiation through custom function definitions, seamless interleave of ML objects with business analytics in object-oriented languages. Delivers significant performance improvements while keeping development within traditional OO code, decreasing hardware/cloud costs. Industrial Mathematics: Allows scientists to focus on mathematical problems rather than optimization while achieving better performance with automatic adjoint calculation. Applications include geophysics, weather forecasting, fluid dynamics, electric impedance tomography. Technical capabilities: automatic full Jacobian calculation at fraction of usual time, PDE solutions on extremely large finite difference grids with quick flawless back-propagation computing sensitivities of PDE solutions relative to PDE coefficients. Sustainability impact: By using MatLogica AADC, organizations reduce carbon footprint, lower electricity bills, extend hardware lifetime, and align with corporate sustainability agendas through green computing practices.

Risk Management & Derivatives Pricing

Finance and Insurance Applications

We can integrate our AADC software into your derivatives pricing and risk management systems. It significantly speeds up complex financial models by 6-100x and allows you to process overnight batches in real-time, do more business, or reduce the cloud/electricity bill by up to 99% while simplifying the software architecture and extending the lifetime of existing hardware. Complex non-linear calculations, such as volatility surface interpolation, yield curve construction, and exotic derivatives pricing, can be supercharged by Matlogica's software enabling significantly faster processing for business-critical XVA calculations and FRTB compliance.

With sustainability high on the corporate agenda, by using MatLogica AADC you will reduce your carbon footprint, electricity bill and extend the lifetime of the existing hardware—supporting green computing initiatives while improving performance.

Speed Up Repetitive Calculations

When performing Monte Carlo simulations, what-if scenarios, stress-testing, back-testing, or historical VaR calculations, MatLogica's code generation kernels will automatically execute 8 (AVX2) or 16 (AVX512) samples of the optimized code in one CPU cycle through vectorization.

Sensitivity and XVA Risk Calculations

Our AAD solution has been tested for large-scale applications calculating sensitivities (Greeks), including close to real-time full portfolio simulations for XVA pricing (CVA, DVA, FVA) and risk calculations under FRTB regulations.

Domain-Specific Languages

You can define your own scripting language for quantitative models and compile it with MatLogica, getting the best of both worlds: run-time flexibility and better-than-native performance for derivatives pricing!

Secure Cloud Execution

MatLogica kernels can be executed in the cloud for scalability, keeping your proprietary quantitative models and sensitive market data secure on-premises.

Model Calibration

You can calibrate complex multi-asset models using Monte Carlo methods and use tick-level market data to perform close to real-time pricing and risk calculations for derivatives portfolios.

Wide Range of Financial Models

MatLogica supports a wide range of quantitative modeling techniques including American Monte Carlo, path-wise Monte Carlo, PDE calculations, stochastic local volatility, and more.

Seamless Interleave with Business Logic

Machine Learning Applications

MatLogica allows easy interleaving of machine learning objects with your business analytics implemented in object-oriented languages like C++. It's like TensorFlow for C++ with automatic differentiation!

Using effective AAD, machine learning models are executed fast: we have demonstrated performance 6x better than TensorFlow for a geophysics application using MatLogica AADC.

MatLogica can deliver a significant performance improvement and decrease the hardware/cloud bill while keeping the actual development within traditional object-oriented code familiar to quants and developers.

Monte Carlo Based Calibration

You can easily calibrate complex multi-asset models relying on Monte Carlo methods and avoid using inflexible and difficult-to-derive analytical approximations for model parameters.

Recalibrate Models in Real-Time

Use real-time tick-level market data to recalibrate your quantitative models and get accurate, up-to-date information for derivatives pricing and risk management.

Create Custom Layers

Efficiently differentiate through custom function definitions in your neural networks, as if they were native layers built into the ML framework from the start.

Excellent Performance for Scientific Computing

Industrial Mathematics Applications

Our software allows scientists to focus on mathematical problems rather than low-level optimization, achieving better performance and calculating adjoints automatically using automatic adjoint differentiation. We can improve the performance of literally any industrial mathematics application from geophysics to weather forecasting, fluid dynamics simulations, and electric impedance tomography.

Optimization Methods

With Matlogica AADC you can automatically calculate the full Jacobian matrix at a fraction of the usual computational time, dramatically accelerating optimization algorithms.

PDEs on Large Grids

MatLogica's AADC processes extremely large finite difference PDE schemes. It executes back-propagation quickly and flawlessly, computing sensitivities of PDE solutions relative to PDE coefficients on grids with millions of nodes.

MatLogica Use Cases: Finance, ML, Industrial Math

We Optimize Your Quantitative Code