Statistical Decision Problems

Selected Concepts and Portfolio Safeguard Case Studies

Business & Finance, Management & Leadership, Operations Research, Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Statistical Decision Problems by Michael Zabarankin, Stan Uryasev, Springer New York
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Michael Zabarankin, Stan Uryasev ISBN: 9781461484714
Publisher: Springer New York Publication: December 16, 2013
Imprint: Springer Language: English
Author: Michael Zabarankin, Stan Uryasev
ISBN: 9781461484714
Publisher: Springer New York
Publication: December 16, 2013
Imprint: Springer
Language: English

Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more.

 

The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more.

 

The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.

More books from Springer New York

Cover of the book Arthrography by Michael Zabarankin, Stan Uryasev
Cover of the book New Directions in Affective Disorders by Michael Zabarankin, Stan Uryasev
Cover of the book Photoemission from Optoelectronic Materials and their Nanostructures by Michael Zabarankin, Stan Uryasev
Cover of the book Towards Understanding the Climate of Venus by Michael Zabarankin, Stan Uryasev
Cover of the book Mixed Effects Models and Extensions in Ecology with R by Michael Zabarankin, Stan Uryasev
Cover of the book Electrochemical Impedance Spectroscopy and its Applications by Michael Zabarankin, Stan Uryasev
Cover of the book Algebraic Combinatorics by Michael Zabarankin, Stan Uryasev
Cover of the book Sustaining Entrepreneurship and Economic Growth by Michael Zabarankin, Stan Uryasev
Cover of the book Induced Pluripotent Stem Cells by Michael Zabarankin, Stan Uryasev
Cover of the book Nonlinear and Complex Dynamics by Michael Zabarankin, Stan Uryasev
Cover of the book Optimal Control with Aerospace Applications by Michael Zabarankin, Stan Uryasev
Cover of the book Mathematics in the Real World by Michael Zabarankin, Stan Uryasev
Cover of the book A Pattern Approach to Lymph Node Diagnosis by Michael Zabarankin, Stan Uryasev
Cover of the book Contemporary Clinical Practice by Michael Zabarankin, Stan Uryasev
Cover of the book Transanal Endoscopic Microsurgery by Michael Zabarankin, Stan Uryasev
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy