國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Numerical probabilityan introduction...

Pages, Gilles.

Numerical probabilityan introduction with applications to finance /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Numerical probabilityby Gilles Pages.
其他題名:	an introduction with applications to finance /
作者:	Pages, Gilles.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xxi, 579 p. :digital ;24 cm.
Contained By:	Springer eBooks
標題:	Probabilities.
電子資源:	http://dx.doi.org/10.1007/978-3-319-90276-0
ISBN:	9783319902760$q(electronic bk.)

Numerical probabilityan introduction with applications to finance /
Pages, Gilles.

Numerical probabilityan introduction with applications to finance /[electronic resource] :by Gilles Pages. - Cham :Springer International Publishing :2018. - xxi, 579 p. :digital ;24 cm. - Universitext,0172-5939. - Universitext..

1 Simulation of random variables -- 2 The Monte Carlo method and applications to option pricing -- 3 Variance reduction -- 4 The Quasi-Monte Carlo method -- 5 Optimal Quantization methods I: cubatures -- 6 Stochastic approximation with applications to finance -- 7 Discretization scheme(s) of a Brownian diffusion -- 8 The diffusion bridge method: application to path-dependent options (II) -- 9 Biased Monte Carlo simulation, Multilevel paradigm -- 10 Back to sensitivity computation -- 11 Optimal stopping, Multi-asset American/Bermuda Options -- 12 Miscellany.

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.

ISBN: 9783319902760$q(electronic bk.)

Standard No.: 10.1007/978-3-319-90276-0doiSubjects--Topical Terms:

182046
Probabilities.

LC Class. No.: QA273 / .P344 2018

Dewey Class. No.: 519.2

Numerical probabilityan introduction with applications to finance /
LDR:02455nmm a2200337 a 4500 001 543121
003 DE-He213
005 20190129163729.0
006 m d
007 cr nn 008maaau
008 190411s2018 gw s 0 eng d
020 $a 9783319902760$q(electronic bk.)
020 $a 9783319902746$q(paper)
024 7 $a 10.1007/978-3-319-90276-0 $2 doi
035 $a 978-3-319-90276-0
040 $a GP $c GP
041 0 $a eng
050 4 $a QA273 $b .P344 2018
072 7 $a PBT $2 bicssc
072 7 $a PBWL $2 bicssc
072 7 $a MAT029000 $2 bisacsh
082 0 4 $a 519.2 $2 23
090 $a QA273 $b .P134 2018
100 1 $a Pages, Gilles. $3 681163
245 1 0 $a Numerical probability $h [electronic resource] : $b an introduction with applications to finance / $c by Gilles Pages.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xxi, 579 p. : $b digital ; $c 24 cm.
490 1 $a Universitext, $x 0172-5939
505 0 $a 1 Simulation of random variables -- 2 The Monte Carlo method and applications to option pricing -- 3 Variance reduction -- 4 The Quasi-Monte Carlo method -- 5 Optimal Quantization methods I: cubatures -- 6 Stochastic approximation with applications to finance -- 7 Discretization scheme(s) of a Brownian diffusion -- 8 The diffusion bridge method: application to path-dependent options (II) -- 9 Biased Monte Carlo simulation, Multilevel paradigm -- 10 Back to sensitivity computation -- 11 Optimal stopping, Multi-asset American/Bermuda Options -- 12 Miscellany.
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 0 $a Probabilities. $3 182046
650 1 4 $a Mathematics. $3 184409
650 2 4 $a Probability Theory and Stochastic Processes. $3 274061
650 2 4 $a Quantitative Finance. $3 274071
650 2 4 $a Statistics for Business/Economics/Mathematical Finance/Insurance. $3 274062
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Universitext. $3 558272
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-90276-0
950 $a Mathematics and Statistics (Springer-11649)