Quantitative Methods in Risk Analysis: A Practitioner's Guide - Leonard C Maclean

. .

Résumé :
The aim of this book is to provide the basic concepts and techniques underlying the quantitative analysis of risk in stochastic dynamic systems. The methods are general, but the emphasis is on financial systems in market economies, and operating systems in transportation. Real world case studies are included. These case studies illustrate how risk analysis is done in practice. Data files are also analysed with the EViews software. Throughout the book, the role of decisions on the outcome from stochastic systems is emphasized. The theme is that decisions have consequences. The standard risk measures for the consequences from downside outcomes are presented, and risk-return models incorporate those measures into optimal decisions. With the inclusion of both conceptual models and practical applications, the book is accessible to senior undergraduate and graduate students in business. In particular, the book is a suitable reference or text for a risk analysis course for masters of business administration students. Some mathematical background is required to understand the models and equations. Experience with statistical reasoning and statistical software is an advantage. There are appendices which summarize relevant mathematical concepts included in the book....

Sommaire:
The aim of this book is to provide the basic concepts and techniques underlying the quantitative analysis of risk in stochastic dynamic systems. The methods are general, but the emphasis is on financial systems in market economies, and operating systems in transportation. Real world case studies are included. These case studies illustrate how risk analysis is done in practice. Data files are also analysed with the EViews software.Throughout the book, the role of decisions on the outcome from stochastic systems is emphasized. The theme is that 'decisions have consequences'. The standard risk measures for the consequences from downside outcomes are presented, and risk-return models incorporate those measures into optimal decisions.With the inclusion of both conceptual models and practical applications, the book is accessible to senior undergraduate and graduate students in business. In particular, the book is a suitable reference or text for a risk analysis course for masters of business administration students.Some mathematical background is required to understand the models and equations. Experience with statistical reasoning and statistical software is an advantage. There are appendices which summarize relevant mathematical concepts included in the book....