Cross Gamma approximations of a portfolio CVA value
A brief presentation by Stephan Bosch that compares the performance of “bumping over AAD” for Tape-Based AAD vs Code Generation AAD to compute second-order greeks focusing on Cross Gamma Hessian entries. MatLogica's Code Generation AAD™ approach delivers sevenfold performance improvement over tape-base AAD.
Presentation: Estimating Expected Shortfall Sensitivities using AADC
Some highlights from the WBS presentation by Svetlana Borovkova from Probability&Partners on Algorithmic Adjoint Differentiation (AAD) For Tail Risk, Model Risk & Stress Testing. Computational costs have been reduced from 8+ hours to <6 seconds using MatLogica AADC!
Presentation: Comparing AAD Techniques & Performance
Some highlights from the WBS presentation by Stephan Bosch comparing Bump & Revalue, traditional tape-based AAD and MatLogica Code Generation AAD™ approaches for XVA calculations.
Case Study: How a Major European Bank Revolutionised Their Front-Office Risk Management Using MatLogica AADC
MatLogica’s AADC enabled the client to supercharge their analytics by introducing AAD for risk computations and to accelerate pricing and scenario analysis. The MatLogica-enhanced analytics unlocked new revenue streams, lowered infrastructure costs, and improved risk management.
Neural Networks: Automatic Synthesis of Neurons for Recurrent Neural Nets
Prof. Roland Olsson and his team used MatLogica's AADC to design state-of-the-art neural network architectures for time series analysis. It is up-to 3x more accurate than the available cutting-edge methods and the training time is several times lower due to MatLogica’s technology.