Machine Learning for Risk Calculations
a practitioner's view
$191.72
- Hardcover
464 pages
- Release Date
28 December 2021
Summary
Unlock Financial Risk Calculation with Machine Learning
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 practic…
Book Details
| ISBN-13: | 9781119791386 |
|---|---|
| ISBN-10: | 1119791383 |
| Series: | The Wiley Finance Series |
| Author: | Ignacio Ruiz, Mariano Zeron |
| Publisher: | John Wiley & Sons Inc |
| Imprint: | John Wiley & Sons Inc |
| Format: | Hardcover |
| Number of Pages: | 464 |
| Release Date: | 28 December 2021 |
| Weight: | 794g |
| Dimensions: | 246mm x 178mm x 41mm |
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About The Author
Ignacio Ruiz
IGNACIO RUIZ, PhD, is the head of Counterparty Credit Risk Measurement and Analytics at Scotiabank. Prior to that he has been head quant for Counterparty Credit Risk Exposure Analytics at Credit Suisse, head of Equity Risk Analytics at BNP Paribas and he founded MoCaX Intelligence, from where he offered his services as an independent consultant. He holds a PhD in Physics from the University of Cambridge.
MARIANO ZERON, PhD, is Head of Research and Development at MoCaX Intelligence. Prior to that he was a quant researcher at Areski Capital. He has extensive experience with Chebyshev Tensors and Deep Neural Nets applied to risk calculations. He holds a PhD in Mathematics from the University of Cambridge.
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