Option pricing and estimation of financial models with R
Stefano M. Iacus
| Year of publication: |
2011 ; Online-Ausg.
|
|---|---|
| Authors: | Iacus, Stefano M. |
| Publisher: |
Chichester, West Sussex, U.K. : Wiley |
| Subject: | Stochastischer Prozess | Stochastic process | Optionspreistheorie | Option pricing theory | Zeitreihenanalyse | Time series analysis | Wahrscheinlichkeitsrechnung | Probability theory |
| Description of contents: |
Includes bibliographical references and index
Table of Contents [swbplus.bsz-bw.de]
; Table of Contents [external.dandelon.com]
|
Online Resource
| Extent: | Online-Ressource (1 online resource (xv, 456 p.)) ill. |
|---|---|
| Type of publication: | Book / Working Paper |
| Language: | English |
| Notes: | Includes index. - Includes bibliographical references and index. - Description based on print version record Option Pricing and Estimation of Financial Models with R; Contents; Preface; 1 A synthetic view; 1.1 The world of derivatives; 1.1.1 Different kinds of contracts; 1.1.2 Vanilla options; 1.1.3 Why options?; 1.1.4 A variety of options; 1.1.5 How to model asset prices; 1.1.6 One step beyond; 1.2 Bibliographical notes; References; 2 Probability, random variables and statistics; 2.1 Probability; 2.1.1 Conditional probability; 2.2 Bayes' rule; 2.3 Random variables; 2.3.1 Characteristic function; 2.3.2 Moment generating function; 2.3.3 Examples of random variables; 2.3.4 Sum of random variables 2.3.5 Infinitely divisible distributions2.3.6 Stable laws; 2.3.7 Fast Fourier Transform; 2.3.8 Inequalities; 2.4 Asymptotics; 2.4.1 Types of convergences; 2.4.2 Law of large numbers; 2.4.3 Central limit theorem; 2.5 Conditional expectation; 2.6 Statistics; 2.6.1 Properties of estimators; 2.6.2 The likelihood function; 2.6.3 Efficiency of estimators; 2.6.4 Maximum likelihood estimation; 2.6.5 Moment type estimators; 2.6.6 Least squares method; 2.6.7 Estimating functions; 2.6.8 Confidence intervals; 2.6.9 Numerical maximization of the likelihood; 2.6.10 The δ-method; 2.7 Solution to exercises 2.8 Bibliographical notesReferences; 3 Stochastic processes; 3.1 Definition and first properties; 3.1.1 Measurability and filtrations; 3.1.2 Simple and quadratic variation of a process; 3.1.3 Moments, covariance, and increments of stochastic processes; 3.2 Martingales; 3.2.1 Examples of martingales; 3.2.2 Inequalities for martingales; 3.3 Stopping times; 3.4 Markov property; 3.4.1 Discrete time Markov chains; 3.4.2 Continuous time Markov processes; 3.4.3 Continuous time Markov chains; 3.5 Mixing property; 3.6 Stable convergence; 3.7 Brownian motion; 3.7.1 Brownian motion and random walks 3.7.2 Brownian motion is a martingale3.7.3 Brownian motion and partial differential equations; 3.8 Counting and marked processes; 3.9 Poisson process; 3.10 Compound Poisson process; 3.11 Compensated Poisson processes; 3.12 Telegraph process; 3.12.1 Telegraph process and partial differential equations; 3.12.2 Moments of the telegraph process; 3.12.3 Telegraph process and Brownian motion; 3.13 Stochastic integrals; 3.13.1 Properties of the stochastic integral; 3.13.2 Itô formula; 3.14 More properties and inequalities for the Itô integral; 3.15 Stochastic differential equations 3.15.1 Existence and uniqueness of solutions3.16 Girsanov's theorem for diffusion processes; 3.17 Local martingales and semimartingales; 3.18 Lévy processes; 3.18.1 Lévy-Khintchine formula; 3.18.2 Lévy jumps and random measures; 3.18.3 Itô-Lévy decomposition of a Lévy process; 3.18.4 More on the Lévy measure; 3.18.5 The Itô formula for Lévy processes; 3.18.6 Lévy processes and martingales; 3.18.7 Stochastic differential equations with jumps; 3.18.8 Itô formula for Lévy driven stochastic differential equations; 3.19 Stochastic differential equations in Rn; 3.20 Markov switching diffusions 3.21 Solution to exercises |
| ISBN: | 978-1-283-40519-5 ; 978-0-470-74584-7 ; 978-1-119-99008-6 ; 0-470-74584-3 ; 978-0-470-74584-7 ; 978-1-119-99008-6 |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012683428