Statistical Decision Problems: Selected Concepts and Portfolio Safeguard Case Studies

✍ Scribed by Michael Zabarankin, Stan Uryasev (auth.)

• Publisher: Springer-Verlag New York
• Year: 2014
• Tongue: English
• Leaves: 254
• Series: Springer Optimization and Its Applications 85
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xiv
Front Matter....Pages 1-1
Random Variables....Pages 3-17
Deviation, Risk, and Error Measures....Pages 19-31
Probabilistic Inequalities....Pages 33-41
Front Matter....Pages 41-41
Maximum Likelihood Method....Pages 45-52
Entropy Maximization....Pages 53-70
Regression Models....Pages 71-87
Classification....Pages 89-99
Statistical Decision Models with Risk and Deviation....Pages 101-129
Front Matter....Pages 131-131
Portfolio Safeguard Case Studies....Pages 133-240
Back Matter....Pages 241-249

✦ Subjects

Operations Research, Management Science; Probability Theory and Stochastic Processes; Data Mining and Knowledge Discovery; Optimization; Operation Research/Decision Theory