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.
[LO 8.2] The Timberlake Corporation has an opportunity to sell its manufacturing facility to Carroll Corporation for $4,500,000. The property has a basis of ...
[LO 9.2] The Timberlake Corporation has an opportunity to sell its manufacturing facility to Carroll Corporation for $4,500,000. The property has a basis of ...
[LO 9.2] The Timberlake Corporation has an opportunity to sell its manufacturing facility to Carroll Corporation for $4,500,000. The property has a basis of ...
1934. Memorandum on the Native Tribes and Tribal Areas of Northern Rhodesia . Lusaka : Government Printer . Timberlake , Michael , ed . 1985.
Timberlake, L. (1987). Only one Earth. London: BBC Books: Earthscan. Tinker, I. (1987). Street foods: Testing assumptions about informal sector by women and ...
The Timberlake Corporation has an opportunity to sell its manufacturing facility to Carroll Corporation for $ 4,500,000 . The property has a basis of ...
Timberlake (1980, 1984) promulgated a behavioral-regulation analysis of learned performance that emphasizes the importance of behavioral.
190; Timberlake 1993, pp. 356–357). By increasing fiscal expenditures, President Carter may have successfully cornered the Fed into delaying tighter ...
( Timberlake , 1993 , p . 4 ) The same was true of the second Bank of the United States , which was chartered in 1816. However , under the leadership of ...
Schlinger, H. and Blakely, E. (1987). Function-altering effects of ... Timberlake, W. and Allison, J. (1974). Response deprivation: An empirical 48 HANDBOOK ...