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Machine Learning for Risk Calculations: A Practitioner's View (The Wiley Finance Series) - Hardcover
- PublisherWiley
- Publication date2021
- ISBN 10 1119791383
- ISBN 13 9781119791386
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages464
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Machine Learning for Risk Calculations : A Practitioner's View
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Machine Learning for Risk Calculations: A Practiti Format: Cloth
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Machine Learning for Risk Calculations : A Practitioner's View
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Machine Learning for Risk Calculations (Hardcover)
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John Wiley & Sons Inc, New York, 2022
ISBN 10: 1119791383
ISBN 13: 9781119791386
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Hardcover. Condition: new. Hardcover. 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 Practitioners 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. Youll 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, youll 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 tensorsDiscover pioneering algorithmic techniques that can create new opportunities in complex risk calculationLearn 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 calculationsRealize 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781119791386
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Machine Learning for Risk Calculations: A Practitioner's View (The Wiley Finance Series)
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Machine Learning for Risk Calculations: A Practitioner's View (The Wiley Finance Series)
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Machine Learning for Risk Calculations
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Machine Learning for Risk Calculations : A Practitioner's View
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Machine Learning for Risk Calculations : A Practitioner's View
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Machine Learning for Risk Calculations: A Practitioner's view
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Hardback. Condition: New. New copy - Usually dispatched within 4 working days. 958. Seller Inventory # B9781119791386
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