Inference for Diffusion Processes
Inference for Diffusion Processes

Author: Christiane Fuchs

Publisher: Springer Science & Business Media

Published: 2013-01-18

Total Pages: 439

ISBN-13: 3642259693

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Diffusion processes are a promising instrument for realistically modelling the time-continuous evolution of phenomena not only in the natural sciences but also in finance and economics. Their mathematical theory, however, is challenging, and hence diffusion modelling is often carried out incorrectly, and the according statistical inference is considered almost exclusively by theoreticians. This book explains both topics in an illustrative way which also addresses practitioners. It provides a complete overview of the current state of research and presents important, novel insights. The theory is demonstrated using real data applications.

Contemporary Quantitative Finance
Contemporary Quantitative Finance

Author: Carl Chiarella

Publisher: Springer Science & Business Media

Published: 2010-07-23

Total Pages: 421

ISBN-13: 3642034780

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This volume contains a collection of papers dedicated to Professor Eckhard Platen to celebrate his 60th birthday, which occurred in 2009. The contributions have been written by a number of his colleagues and co-authors. All papers have been - viewed and presented as keynote talks at the international conference “Quantitative Methods in Finance” (QMF) in Sydney in December 2009. The QMF Conference Series was initiated by Eckhard Platen in 1993 when he was at the Australian - tional University (ANU) in Canberra. Since joining UTS in 1997 the conference came to be organised on a much larger scale and has grown to become a signi?cant international event in quantitative ?nance. Professor Platen has held the Chair of Quantitative Finance at the University of Technology, Sydney (UTS) jointly in the Faculties of Business and Science since 1997. Prior to this appointment, he was the Founding Head of the Centre for Fin- cial Mathematics at the Institute of Advanced Studies at ANU, a position to which he was appointed in 1994. Eckhard completed a PhD in Mathematics at the Technical University in Dresden in 1975 and in 1985 obtained his Doctor of Science degree (Habilitation degree in the German system) from the Academy of Sciences in Berlin where he headed the Stochastics group at the Weierstrass Institute.

Statistical Methods for Stochastic Differential Equations
Statistical Methods for Stochastic Differential Equations

Author: Mathieu Kessler

Publisher: CRC Press

Published: 2012-05-17

Total Pages: 509

ISBN-13: 1439849404

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The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a spectrum of estimation methods, including nonparametric estimation as well as parametric estimation based on likelihood methods, estimating functions, and simulation techniques. Two chapters are devoted to high-frequency data. Multivariate models are also considered, including partially observed systems, asynchronous sampling, tests for simultaneous jumps, and multiscale diffusions. Statistical Methods for Stochastic Differential Equations is useful to the theoretical statistician and the probabilist who works in or intends to work in the field, as well as to the applied statistician or financial econometrician who needs the methods to analyze biological or financial time series.

Statistical Inference for Ergodic Diffusion Processes
Statistical Inference for Ergodic Diffusion Processes

Author: Yury A. Kutoyants

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 493

ISBN-13: 144713866X

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The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.

Statistical Inference for Diffusion Type Processes
Statistical Inference for Diffusion Type Processes

Author: B.L.S. Prakasa Rao

Publisher: Wiley

Published: 2010-05-24

Total Pages: 0

ISBN-13: 9780470711125

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Decision making in all spheres of activity involves uncertainty. If rational decisions have to be made, they have to be based on the past observations of the phenomenon in question. Data collection, model building and inference from the data collected, validation of the model and refinement of the model are the key steps or building blocks involved in any rational decision making process. Stochastic processes are widely used for model building in the social, physical, engineering, and life sciences as well as in financial economics. Statistical inference for stochastic processes is of great importance from the theoretical as well as from applications point of view in model building. During the past twenty years, there has been a large amount of progress in the study of inferential aspects for continuous as well as discrete time stochastic processes. Diffusion type processes are a large class of continuous time processes which are widely used for stochastic modelling. the book aims to bring together several methods of estimation of parameters involved in such processes when the process is observed continuously over a period of time or when sampled data is available as generally feasible.

Handbook of Financial Econometrics
Handbook of Financial Econometrics

Author: Yacine Ait-Sahalia

Publisher: Elsevier

Published: 2009-10-19

Total Pages: 809

ISBN-13: 0080929842

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This collection of original articles—8 years in the making—shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume. - Presents a broad survey of current research—from local characterizations of the Markov process dynamics to financial market trading activity - Contributors include Nobel Laureate Robert Engle and leading econometricians - Offers a clarity of method and explanation unavailable in other financial econometrics collections

A Portrait of State-of-the-Art Research at the Technical University of Lisbon
A Portrait of State-of-the-Art Research at the Technical University of Lisbon

Author: Manuel Seabra Pereira

Publisher: Springer Science & Business Media

Published: 2007-11-24

Total Pages: 605

ISBN-13: 1402056907

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This book celebrates the 75th anniversary of The Technical University of Lisbon (UTL). It provides a compelling picture of current state-of-art research at UTL. It contains the edited version of the invited lectures from a two day Symposium and brings together a comprehensive summary of high quality research contributions across basic and applied sciences. A broad spectrum of topics is covered reflecting UTL’s worldwide recognition.

Stochastic Epidemic Models with Inference
Stochastic Epidemic Models with Inference

Author: Tom Britton

Publisher: Springer Nature

Published: 2019-11-30

Total Pages: 477

ISBN-13: 3030309002

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Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.

Statistical Inference for Fractional Diffusion Processes
Statistical Inference for Fractional Diffusion Processes

Author: B. L. S. Prakasa Rao

Publisher: John Wiley & Sons

Published: 2011-07-05

Total Pages: 213

ISBN-13: 0470975768

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Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial economics. In model building, statistical inference for stochastic processes is of great importance from both a theoretical and an applications point of view. This book deals with Fractional Diffusion Processes and statistical inference for such stochastic processes. The main focus of the book is to consider parametric and nonparametric inference problems for fractional diffusion processes when a complete path of the process over a finite interval is observable. Key features: Introduces self-similar processes, fractional Brownian motion and stochastic integration with respect to fractional Brownian motion. Provides a comprehensive review of statistical inference for processes driven by fractional Brownian motion for modelling long range dependence. Presents a study of parametric and nonparametric inference problems for the fractional diffusion process. Discusses the fractional Brownian sheet and infinite dimensional fractional Brownian motion. Includes recent results and developments in the area of statistical inference of fractional diffusion processes. Researchers and students working on the statistics of fractional diffusion processes and applied mathematicians and statisticians involved in stochastic process modelling will benefit from this book.

Bayesian Time Series Models
Bayesian Time Series Models

Author: David Barber

Publisher: Cambridge University Press

Published: 2011-08-11

Total Pages: 432

ISBN-13: 0521196760

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The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.