000			01674 a2200277 4500
003			OSt
005			20250304020004.0
008			250219b xxu||||| |||| 00| 0 eng d
020			_a9783319902746
040			_cIIT Kanpur
041			_aeng
082			_a519.2 _bP147n
100			_aPages, Gilles
245			_aNumerical probability _ban introduction with applications to finance _cGilles Pages
260			_bSpringer _c2018 _aSwitzerland
300			_axxi, 579p
440			_aUniversitext
490			_a / edited by Sheldon Axler... [et al.]
520			_a This textbook provides a self-contained introduction to numerical methods in probability with a focus on applications to finance. Topics covered include the Monte Carlo simulation (including simulation of random variables, variance reduction, quasi-Monte Carlo simulation, and more recent developments such as the multilevel paradigm), stochastic optimization and approximation, discretization schemes of stochastic differential equations, as well as optimal quantization methods. The author further presents detailed applications to numerical aspects of pricing and hedging of financial derivatives, risk measures (such as value-at-risk and conditional value-at-risk), implicitation of parameters, and calibration. Aimed at graduate students and advanced undergraduate students, this book contains useful examples and over 150 exercises, making it suitable for self-study.
650			_aProbabilities
650			_aMathematics applied
650			_aFinance and accounting
650			_aMathematics probability and statistics general
650			_aProbability and statistics
942			_cBK _01
999			_c567374 _d567374