SABR and SABR LIBOR Market Models in Practice ─ With Examples Implemented in Python

Interest Rate vanilla traders have been using the SABR model for more than a decade. The SABR model is commonly used for vanilla products where the LMM model is commonly used for exotic products; however, this system often causes inconsistencies which can be overcome with a joint SABR LIBOR Market Model. Knowledge of these models is essential to all aspiring interest rate quants and traders, as well an understanding of their failings and alternatives.

This book is an accessible guide to interest rate modelling. Rather than covering an array of models which are not very often used in practice, it focuses on the SABR model, the market standard for vanilla products. It also covers the LIBOR Market Model, the most commonly used model for exotic products, as well as examining the extended SABR LIBOR Market Model. This book takes a hands-on approach, demonstrating simply how to implement and work with the models in practice. It provides a comprehensive guide to how interest rate modelling is done in practice on the trading floor.

Christian Crispoldi is Vice President at Nomura in New York where he is responsible for the valuation and pricing of interest rate derivatives. Previously he worked as a financial engineer in various bank across Europe. Christian holds a masters degree in Mathematical Finance from the University of York, UK, and a bachelor degree in Computer Engineering from the University of Bologna, Italy.

Peter Larkin is a Data Scientist working on building predictive models using big data in the (re)insurance industry. Previously he worked as a Quantitative Analyst in the financial services industry working on projects spanning the pricing of structured products, credit and market risk, and asset management. Peter has a background in Theoretical Physics and received his Ph.D from the University of York in 2008, previously having studied at Cambridge University and Imperial College London. In 2012 he also completed a MSc in Mathematical Finance from the University of Oxford.


Gerald Wigger is Head of Quantitative Analysis at Weisshorn Re. He previously worked in various responsible roles such as Head of Pricing at Axa Winterthur, Head of Risk Modeling at Zurcher Kantonalbank and Interest Rate Derivatives Quant at Bank of America Merril Lynch. Gerald Wigger holds a PhD in Solid State Physics from ETH Zuerich.