Statistical methods for stochastic differential equations. (2012)

• Record Type: Book
• Further Information: Note: Edited by Mathieu Kessler, Alexander Lindner, Michael Sørensen.
• Other Names: Kessler, Mathieu, 1970-; Lindner, Alexander, 1973-; Sørensen, Michael
• Contents: Estimating functions for diffusion-type processes, Michael Sørensen ; Introduction; Low frequency asymptotics; Martingale estimating functions; The likelihood function; Non-martingale estimating functions; High-frequency asymptotics; High-frequency asymptotics in a fixed time-interval; Small-diffusion asymptotics; Non-Markovian models; General asymptotic results for estimating functions; Optimal estimating functions: General theory; ; The econometrics of high frequency data, Per. A. Mykland and Lan Zhang ; Introduction; Time varying drift and volatility; Behavior of estimators: Variance; Asymptotic normality; Microstructure; Methods based on contiguity; Irregularly spaced data; ; Statistics and high frequency data, Jean Jacod; Introduction; What can be estimated?; Wiener plus compound Poisson processes; Auxiliary limit theorems; A first LNN (Law of Large Numbers); Some other LNNs; A first CLT; CLT with discontinuous limits; Estimation of the integrated volatility; Testing for jumps; Testing for common jumps; The Blumenthal–Getoor index; ; Importance sampling techniques for estimation of diffusion models, Omiros Papaspiliopoulos and Gareth Roberts; Overview of the chapter; Background; IS estimators based on bridge processes; IS estimators based on guided processes; Unbiased Monte Carlo for diffusions; Appendix: Typical problems of the projection-simulation paradigm in MC for diffusions; Appendix: Gaussian change of measure; ; Non parametric estimation of the coefficients of ergodic diffusion processes based on high frequency data, Fabienne Comte, Valentine Genon-Catalot, and Yves Rozenholc; Introduction; Model and assumptions; Observations and asymptotic framework; Estimation method; Drift estimation; Diffusion coefficient estimation; Examples and practical implementation; Bibliographical remarks; Appendix. Proof of Proposition.13; ; Ornstein–Uhlenbeck related models driven by Lévy processes, Peter J. Brockwell and Alexander Lindner ; Introduction; Lévy processes; Ornstein–Uhlenbeck related models; Some estimation methods; ; Parameter estimation for multiscale diffusions: an overview, Grigorios A. Pavliotis, Yvo Pokern, and Andrew M. Stuart; Introduction; Illustrative examples; Averaging and homogenization; Subsampling; Hypoelliptic diffusions; Nonparametric drift estimation; Conclusions and further work;
• Publisher Details: Boca Raton : CRC Press
• Publication Date: 2012
• Extent: 1 online resource (xxiv, 472 pages)
• Subjects: 515/.35; Stochastic differential equations -- Statistical methods; Stochastic Processes; Models, Theoretical; Electronic books
• Languages: English
• ISBNs: 1439849765; 9781439849767
• Related ISBNs: 9781439849408; 9781439849767
• Notes: Note: Includes bibliographical references.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.