£60.00

MACMILLAN SABR and SABR LIBOR Market Models in Practice: With Examples Implemented in Python (Applied Quantitative Finance)

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£103.56 £55.63 £66.09 £76.55 £87.00 £97.46 £107.92 01 October 2024 01 February 2025 05 June 2025 06 October 2025 07 February 2026

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234 days · current 19 days 14 days 34 days 183 days 11 days 0 59 117 176 234 £60 £75 £78 £83 £84 £104 Days at Price

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Most common price: £60 (234 days, 47.3%)

Price range: £60 - £104

Price levels: 6 different prices over 495 days

Description

Interest rate traders have been using the SABR model to price vanilla products for more than a decade. However this model suffers however from a severe limitation: its inability to value exotic products. A term structure model à la LIBOR Market Model (LMM) is often employed to value these more complex derivatives, however the LMM is unable to capture the volatility smile. A joint SABR LIBOR Market Model is the natural evolution towards a consistent pricing of vanilla and exotic products. Knowledge of these models is essential to all aspiring interest rate quants, traders and risk managers, as well an understanding of their failings and alternatives. SABR and SABR Libor Market Models in Practice is an accessible guide to modern interest rate modelling. Rather than covering an array of models which are seldom used in practice, it focuses on the SABR model, the market standard for vanilla products, the LIBOR Market Model, the most commonly used model for exotic products andthe extended SABR LIBOR Market Model. The book takes a hands-on approach, demonstrating simply how to implement and work with these models in a market setting. It bridges the gap between the understanding of the models from a conceptual and mathematical perspective and the actual implementation by supplementing the interest rate theory with modelling specific, practical code examples written in Python.

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
29 September 2015
Listed Since
05 March 2015

Barcode

No barcode data available

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