Statistical decision problems : selected concepts and portfolio safeguard case studies - Zabarankin Michael; Usyasev, Stan (New York : Springer, 2014)
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.
References 241-244p.; Index 245-249p.
Keywords: Maximum likelihood methods; Regression models; Probabilistic inequalities