<電子ブック>
Numerical Solution of Stochastic Differential Equations with Jumps in Finance / by Eckhard Platen, Nicola Bruti-Liberati
(Stochastic Modelling and Applied Probability. ISSN:2197439X ; 64)
版 | 1st ed. 2010. |
---|---|
出版者 | Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer |
出版年 | 2010 |
本文言語 | 英語 |
大きさ | XXVI, 856 p. 169 illus : online resource |
著者標目 | *Platen, Eckhard author Bruti-Liberati, Nicola author SpringerLink (Online service) |
件 名 | LCSH:Probabilities LCSH:Mathematics LCSH:Statistics LCSH:Social sciences -- Mathematics 全ての件名で検索 FREE:Probability Theory FREE:Applications of Mathematics FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Mathematics in Business, Economics and Finance |
一般注記 | Stochastic Differential Equations with Jumps -- Exact Simulation of Solutions of SDEs -- Benchmark Approach to Finance and Insurance -- Stochastic Expansions -- to Scenario Simulation -- Regular Strong Taylor Approximations with Jumps -- Regular Strong Itô Approximations -- Jump-Adapted Strong Approximations -- Estimating Discretely Observed Diffusions -- Filtering -- Monte Carlo Simulation of SDEs -- Regular Weak Taylor Approximations -- Jump-Adapted Weak Approximations -- Numerical Stability -- Martingale Representations and Hedge Ratios -- Variance Reduction Techniques -- Trees and Markov Chain Approximations -- Solutions for Exercises In financial and actuarial modeling and other areas of application, stochastic differential equations with jumps have been employed to describe the dynamics of various state variables. The numerical solution of such equations is more complex than that of those only driven by Wiener processes, described in Kloeden & Platen: Numerical Solution of Stochastic Differential Equations (1992). The present monograph builds on the above-mentioned work and provides an introduction to stochastic differential equations with jumps, in both theory and application, emphasizing the numerical methods needed to solve such equations. It presents many new results on higher-order methods for scenario and Monte Carlo simulation, including implicit, predictor corrector, extrapolation, Markov chain and variance reduction methods, stressing the importance of their numerical stability. Furthermore, it includes chapters on exact simulation, estimation and filtering. Besides serving as a basic text on quantitativemethods, it offers ready access to a large number of potential research problems in an area that is widely applicable and rapidly expanding. Finance is chosen as the area of application because much of the recent research on stochastic numerical methods has been driven by challenges in quantitative finance. Moreover, the volume introduces readers to the modern benchmark approach that provides a general framework for modeling in finance and insurance beyond the standard risk-neutral approach. It requires undergraduate background in mathematical or quantitative methods, is accessible to a broad readership, including those who are only seeking numerical recipes, and includes exercises that help the reader develop a deeper understanding of the underlying mathematics HTTP:URL=https://doi.org/10.1007/978-3-642-13694-8 |
目次/あらすじ
所蔵情報を非表示
電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
電子ブック | オンライン | 電子ブック |
|
|
Springer eBooks | 9783642136948 |
|
電子リソース |
|
EB00233518 |
書誌詳細を非表示
データ種別 | 電子ブック |
---|---|
分 類 | LCC:QA273.A1-274.9 DC23:519.2 |
書誌ID | 4000114935 |
ISBN | 9783642136948 |
類似資料
この資料の利用統計
このページへのアクセス回数:2回
※2017年9月4日以降