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Cover image for product 0470977612
Morini
ISBN: 978-0-470-97761-3
Hardcover
448 pages
October 2011
List Price: 85.00 USD
11,050,000 IRR / 3,060,000 IRR افزودن به سبد
  • Description
  • Table of Contents
  • Author Information
The proliferation of increasingly complex pricing models has vastly expanded the operational capabilities of financial institutions within financial markets. However, it has also increased the industry’s reliance on quantitative instruments, and created massive model risk. Consequently, model validation and model risk management are crucial tools for success in the market.

Understanding and Managing Model Risk: A Practical Guide for Quants, Traders and Validators brings together a wide range of detailed real world examples, quantitative analysis and regulatory issues. It investigates the interaction between mathematics and the reality of markets, including the explanation of model errors and misunderstandings, providing readers with the operative indications and practical insight to help mitigate the likelihood of model losses.

Taking an operative as opposed to a bureaucratic approach to model validation, the book:

  • Examines the risks arising from the use of models in calibration, pricing, hedging, correlation modelling, extrapolation and statistical arbitrage.
  • Tackles modern day modelling issues including funding and market liquidity, CSA discounting, basis risk, counterparty risk, approximation errors, regulatory uncertainties and stress-testing.
  • Investigates consensus models and how consensus can suddenly break down.
  • Explores in detail examples from interest rate, credit and hybrid markets, covering also equity and cross-currency risks.
  • Analyzes and compares a range of models including stochastic and local volatility, jumps, Libor and SABR models, copulas, structural and reduced-form models.

Understanding and Managing Model Risk offers an in-depth understanding of the financial implications of mathematical assumptions, and provides the right tools to identify, quantify and manage the risks inherent in the use of quantitative models.

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