Machine Learning for Risk Calculations: A Practitioner's View (The Wiley Finance Series)
by Ignacio Ruiz and Mariano Zeron
$71.40 / copy at 25+ copies As low as $67.20 at 1,000+Your best volume price
Total $1,785.00
Format
The more copies, the less each one costs
Applied automatically in your cart. No code needed.
Turn this order into a program
Groups that order together often pair the copies with something more. We handle the extras so you don't have to.
Bookplates, tipped-in pages, belly bands or author signatures. Subject to publisher approval.
Customization options Ship to every readerOne address, many sites or individual recipients' homes, in the US and abroad.
Fulfillment options Pair it with a branded journalJournals with your logo or each reader's name, for the same group.
Branded journals
Bring in a speaker
BookPal is partnering with Talezo to help you find and book authors, speakers and performers for your event.
BookPal × TalezoMachine Learning for Risk Calculations
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. Machine Learning for 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.
Details
- Publisher
- Wiley
- Authors
- Ignacio Ruiz, Mariano Zeron
- Format
- Hardcover
- Published
- Jan 5, 2022
- ISBN-13
- 9781119791386
- Pages
- 464
- Carton quantity
- 8 copies
Machine Learning for Risk Calculations for groups: pricing
Volume pricing applies automatically in your cart. No codes, no account needed.
| Copies | Price per copy | You save |
|---|---|---|
| 25 – 99 | $71.40 | 15% off list |
| 100 – 249 | $70.56 | 16% off list |
| 250 – 499 | $69.72 | 17% off list |
| 500 – 999 | $68.88 | 18% off list |
| 1,000+ | $67.20 | 20% off list |
Popular for
For new managers and leadership cohorts, a chapter per session.
A shared vocabulary for the whole organization.
A takeaway attendees will actually read, delivered to your venue.
Where can I buy 100 copies of Machine Learning for Risk Calculations?
BookPal sells Machine Learning for Risk Calculations in quantity. At 100 copies the price is $70.56 a copy, against a list price of $84.00, and the cart applies the volume tier automatically. Free shipping on most orders over $95 in the contiguous US. A specialist can quote a larger or mixed order.
- New books only, straight from the publisher
- Volume prices apply automatically in the cart, with no code needed
- Order at least 10 business days before you need the books (11 from mid-November through December)
What does Machine Learning for Risk Calculations cost when I buy for a group?
Volume pricing applies automatically in your cart, with no code needed. Price per copy: 25 to 99 copies, $71.40 (15% off list); 100 to 249 copies, $70.56 (16% off list); 250 to 499 copies, $69.72 (17% off list); 500 to 999 copies, $68.88 (18% off list); 1,000+ copies, $67.20 (20% off list). Need a different quantity, or a quote to forward for approval? Ask a specialist and we will confirm pricing before you pay.
How fast can I get copies of Machine Learning for Risk Calculations?
Need them by a specific date? Request a quote and we'll confirm timing before you pay.
Can you ship to several locations or people's homes?
Yes. We ship group orders to one address, to multiple sites, or to individual recipients, in the US and internationally. See fulfillment options.
Can I get a formal quote for approval before ordering?
Yes. Request a quote and we'll send a PDF you can forward for approval.
Do you accept purchase orders and tax-exempt orders?
Yes. We accept purchase orders upon approval, as well as cards, PayPal, ACH, wire transfers and checks. BookPal is a tax-exempt supplier in all 50 states. See purchase orders and sales tax exemption.
What if I find a lower price?
Send us the link. We match prices from other booksellers and distributors on a new copy in the same edition, available to ship in the quantity you need. Clearance sales and pricing errors are the exception, and we'll tell you quickly if that's the case. Start a price match.
Write a Review
Machine Learning for Risk Calculations: A Practitioner's View (The Wiley Finance Series)
Teams also order
A colleague asked you to approve this order
Your quote list
Add books as you browse, then request one quote for all of them.