Overview
This book covers the method of metric distances and its application in probability theory and other fields. The method is fundamental in the study of limit theorems and generally in assessing the quality of approximations to a given probabilistic model. The method of metric distances is developed to study stability problems and reduces to the selection of an ideal or the most appropriate metric for the problem under consideration and a comparison of probability metrics. After describing the basic structure of probability metrics and providing an analysis of the topologies in the space of probability measures generated by different types of probability metrics, the authors study stability problems by providing a characterization of the ideal metrics for a given problem and investigating the main relationships between different types of probability metrics. The presentation is provided in a general form, although specific cases are considered as they arise in the process of finding supplementary bounds or in applications to important special cases. Svetlozar T. Rachev is the Frey Family Foundation Chair of Quantitative Finance, Department of Applied Mathematics and Statistics, SUNY-Stony Brook and Chief Scientist of Finanlytica, USA. Lev B. Klebanov is a Professor in the Department of Probability and Mathematical Statistics, Charles University, Prague, Czech Republic. Stoyan V. Stoyanov is a Professor at EDHEC Business School and Head of Research, EDHEC-Risk Institute—Asia (Singapore). Frank J. Fabozzi is a Professor at EDHEC Business School. (USA)
Full Product Details
Author: Svetlozar T. Rachev ,
Lev Klebanov ,
Stoyan V. Stoyanov ,
Frank Fabozzi
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 2013 ed.
Dimensions:
Width: 15.50cm
, Height: 3.40cm
, Length: 23.50cm
Weight: 1.112kg
ISBN: 9781461448686
ISBN 10: 1461448689
Pages: 619
Publication Date: 03 January 2013
Audience:
College/higher education
,
Postgraduate, Research & Scholarly
Format: Hardback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Reviews
From the book reviews: This textbook gives a comprehensive overview of the method of metric distances and its applications in probability theory. ... The text is mainly self-contained and should be accessible for readers with basic knowledge in probability theory. The exposition is well structured and covers an impressive range of topics around the central theme of probability metrics. (Hilmar Mai, zbMATH, Vol. 1280, 2014) The reviewed book is divided into five parts. ... The target audience is graduate students in the areas of functional analysis, geometry, mathematical programming, probability, statistics, stochastic analytics, and measure theory. The book can also be used for students in probability and statistics. The theory of probability metrics presented here can be applied to engineering, physics, chemistry, information theory, economics, and finance. Specialists from the aforementioned areas might find the book useful. (Adriana Hornikova, Technometrics, Vol. 55 (4), November, 2013)
From the book reviews: This textbook gives a comprehensive overview of the method of metric distances and its applications in probability theory. ... The text is mainly self-contained and should be accessible for readers with basic knowledge in probability theory. The exposition is well structured and covers an impressive range of topics around the central theme of probability metrics. (Hilmar Mai, zbMATH, Vol. 1280, 2014) The reviewed book is divided into five parts. ... The target audience is graduate students in the areas of functional analysis, geometry, mathematical programming, probability, statistics, stochastic analytics, and measure theory. The book can also be used for students in probability and statistics. The theory of probability metrics presented here can be applied to engineering, physics, chemistry, information theory, economics, and finance. Specialists from the aforementioned areas might find the book useful. (Adriana Hornikova, Technometrics, Vol. 55 (4), November, 2013)
From the reviews: This textbook gives a comprehensive overview of the method of metric distances and its applications in probability theory. ... The text is mainly self-contained and should be accessible for readers with basic knowledge in probability theory. The exposition is well structured and covers an impressive range of topics around the central theme of probability metrics. (Hilmar Mai, zbMATH, Vol. 1280, 2014)
From the book reviews: “This textbook gives a comprehensive overview of the method of metric distances and its applications in probability theory. … The text is mainly self-contained and should be accessible for readers with basic knowledge in probability theory. The exposition is well structured and covers an impressive range of topics around the central theme of probability metrics.” (Hilmar Mai, zbMATH, Vol. 1280, 2014) “The reviewed book is divided into five parts. … The target audience is graduate students in the areas of functional analysis, geometry, mathematical programming, probability, statistics, stochastic analytics, and measure theory. The book can also be used for students in probability and statistics. The theory of probability metrics presented here can be applied to engineering, physics, chemistry, information theory, economics, and finance. Specialists from the aforementioned areas might find the book useful.” (Adriana Horníková, Technometrics, Vol. 55 (4), November, 2013)
Author Information
Svetlozar T. Rachev is a Professorin Department of Applied Mathematics and Statistics, SUNY-Stony Brook. Lev B. Klebanov is a Professor in the Department of Probability and Mathematical Statistics, MFF, Charles University, Prague, Czech Republic. Stoyan V. Stoyanov is a Professor of Finance, EDHEC Business School, Head of Research, EDHEC-Risk Institute. Frank J. Fabozzi is a Professor of Finance, EDHEC Business School
