Mathematical Finance & Financial Data Science Seminar
Parametric Differential Machine Learning for Pricing and Calibration
Speaker: Arun Polala, Wells Fargo Bank
Location: Online Zoom access provided to registrants
Date: Tuesday, May 2, 2023, 5:30 p.m.
We developed a Parametric Differential Machine Learning methodology to learn DNN parametric pricers for varying model and contract parameters, with adaptive parameter sampling. We demonstrated these parametric pricers and used them for calibration for the example of specific Cheyette models for interest rate caplets. We used the inherent randomness of the process to optimize over several random replications and thus robustify the calibration. Models and instruments are given in low-code close to mathematical notation and then translated to efficient differentiable simulation and computation in TensorFlow. This is a joint work with Bernhard Hientzsch.
Arun is a quantitative analyst with three years of experience in the banking industry. He graduated from Florida State University with a PhD degree in Financial Mathematics. As a quantitative analyst, he is responsible for developing financial models for pricing and risk management using advanced Machine Learning techniques.
For the reference material, please refer to our publication on SSRN: Click here