
Workshop Day: Wednesday 19th October:
The workshop day is complimentary to all conference attendees, numbers limited so first come first served.
Machine Learning Models for the Interest Rates: 13.30 – 17.30
Session One: Machine Learning Architecture (VAE, VEGD) – 13:30 to 15:00
- Variational autoencoder architecture (VAE)
- The roles of encoder and decoder, latent space
- Deliberately introducing uncertainty in reconstruction
- Loss function and optimization loop
- Reconstruction with VAE
- Generation with VAE
- Variational encoder-generator-decoder architecture (VEGD)
- The role of generator between encoder and decoder
- Generator parameterization
- Generator training
- Hands-on examples with Python
- VAE for handwritten digits from the MNIST dataset
- VEGD for arithmetic on handwritten digits from the MNIST dataset
Coffee Break – 15:00 to 15:30
Session Two: Application to Interest Rate Models – 15:30 to 17:00
- Principles of interest rate model construction
- Stochastic drivers and state variables
- Historical calibration in P-measure
- Arbitrage-free calibration in Q-measure
- Three types of interest rate models and connection between them
- One factor short rate models
- SDE models: HW, BK, CIR++
- Machine learning (VEGD) models
- Two factor short rate models
- SDE models: HW2F/G2, CIR2++
- Machine learning (VEGD) models
- Forward rate models
- Single rate SDE models: Black, SABR
- Forward curve SDE models: HJM, LMM, SABR-LMM
- Machine learning (VEGD) models
- Curve basis models
- Static models: Nelson-Siegel (NS), Nelson-Siegel-Svensson (NSS)
- SDE models: AFNS, Factor HJM
- Machine learning (VAE) counterparts of static models
- Machine learning (VEGD) counterparts of SDE models
- Hands-on examples with Python
- VAE for the yield curve with one and two dimensional latent space
- Historical VEGD model training in P-measure
- Arbitrage-free market implied VEGD model calibration in Q-measure
Q&A – 17:00 to 17:30

Alexander Sokol:
Executive Chairman and Head of Quant Research, CompatibL
Understanding ESG & Climate Risk: 13.30 – 17.30
- Understanding the importance of ESG as pillar of the banking prudential framework
- Classification and assessment of ESG risks
- Analysis of the potential impact of the ESG risks
- How to integrate climate change in risk management and disclose it as for the TCFD recommendations.
COURSE OBJECTIVE
- Get a foundation of the ESG and climate change theory and more frequent applications
- Understanding the recommendations of the EBA and Task force on climate-related financial disclosures (TCFD).
- Understand the key categories of ESG risks and how to measure and report them

Navin Rauniar:
Advisory Partner focusing on LIBOR, ESG, Climate Risk & TCFD, HSBC