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Machine Learning for Risk Calculations

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$94.68

Last updated on September 18, 2022 7:31 am
SKU: 35184805

$94.68

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State-of-the-art algorithmic deep learning and tensoring techniques for financial institutions
The computational demand of risk calculations in financial institutions has ballooned and shows no sign of stopping. It is no longer viable to simply add more computing power to deal with this increased demand. The solution? Algorithmic solutions based on deep learning and Chebyshev tensors represent a practical way to reduce costs while simultaneously increasing risk calculation capabilities. Deep Learning and Tensoring Risk Calculations: A Practitioner’s View provides an in-depth review of a number of algorithmic solutions and demonstrates how they can be used to overcome the massive computational burden of risk calculations in financial institutions.
This book will get you started by reviewing fundamental techniques, including deep learning and Chebyshev tensors. You’ll then discover algorithmic tools that, in combination with the fundamentals, deliver actual solutions to the real problems financial institutions encounter on a regular basis. Numerical tests and examples demonstrate how these solutions can be applied to practical problems, including XVA and Counterparty Credit Risk, IMM capital, PFE, VaR, FRTB, Dynamic Initial Margin, pricing function calibration, volatility surface parametrisation, portfolio optimisation and others. Finally, you’ll uncover the
benefits these techniques provide, the practicalities of implementing them, and the software which can be used.

Review the fundamentals of deep learning and Chebyshev tensors
Discover pioneering algorithmic techniques that can create new opportunities in complex risk calculation
Learn how to apply the solutions to a wide range of real-life risk calculations.
Download sample code used in the book, so you can follow along and experiment with your own calculations
Realize improved risk management whilst overcoming the burden of limited computational power
Quants, IT professionals, and financial risk managers will benefit from this practitioner-oriented approach to state-of-the-art risk calculation.

Specification: Machine Learning for Risk Calculations

Release date NZ

December 23rd, 2021

Author

Ignacio Ruiz Mariano Zeron

Audience

Professional & Vocational

Country of Publication

United States

Imprint

John Wiley & Sons Inc

Pages

304

Series

The Wiley Finance Series

Dimensions

165x220x25

ISBN-13

9781119791386

Product ID

35184805

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Machine Learning for Risk Calculations

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