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Numerical Probability
By Gilles Pagès
0 - Default Title
Description
The volume covers a broad range of topics, including Monte Carlo simulation techniques—such as the simulation of random variables, variance reduction strategies, quasi-Monte Carlo methods—and recent advancements like the multilevel Monte Carlo paradigm. It further discusses discretization schemes for stochastic differential equations and optimal quantization methods. A rigorous treatment of stochastic optimization is provided, encompassing stochastic gradient descent, including Langevin-based gradient descent algorithms, new to this edition. Detailed applications are presented in the context of numerical methods for pricing and hedging financial derivatives, the computation of risk measures (including value-at-risk and conditional value-at-risk), parameter implicitation, and model calibration.
Intended for graduate students and advanced undergraduates, the textbook includes numerous illustrative examples and over 200 exercises, rendering it well-suited for both classroom use and independent study.
Product details
Binding:
Paperback
Edition:
2
Number of Pages:
660
Release Date:
2025-11-21
Publication Date:
2025-11-21
Publisher:
Springer
Languages:
Original:
English
ISBN10:
3032100917
ISBN13:
9783032100917
GPSR Manufacturer Reference:
Weight:
1104 g
Height:
155 cm
Width:
235 cm
Thickness:
33 cm
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