Practical spreadsheet risk modeling for management
著者
書誌事項
Practical spreadsheet risk modeling for management
Chapman & Hall/CRC, c2012
- : hbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Risk analytics is developing rapidly, and analysts in the field need material that is theoretically sound as well as practical and straightforward. A one-stop resource for quantitative risk analysis, Practical Spreadsheet Risk Modeling for Management dispenses with the use of complex mathematics, concentrating on how powerful techniques and methods can be used correctly within a spreadsheet-based environment.
Highlights
Covers important topics for modern risk analysis, such as frequency-severity modeling and modeling of expert opinion
Keeps mathematics to a minimum while covering fairly advanced topics through the use of powerful software tools
Contains an unusually diverse selection of topics, including explicit treatment of frequency-severity modeling, copulas, parameter and model uncertainty, volatility modeling in time series, Markov chains, Bayesian modeling, stochastic dominance, and extended treatment of modeling expert opinion
End-of-chapter exercises span eight application areas illustrating the broad application of risk analysis tools with the use of data from real-world examples and case studies
This book is written for anyone interested in conducting applied risk analysis in business, engineering, environmental planning, public policy, medicine, or virtually any field amenable to spreadsheet modeling. The authors provide practical case studies along with detailed instruction and illustration of the features of ModelRisk (R), the most advanced risk modeling spreadsheet software currently available. If you intend to use spreadsheets for decision-supporting analysis, rather than merely as placeholders for numbers, then this is the resource for you.
目次
Conceptual Maps and Models. Basic Monte Carlo Simulation in Spreadsheets. Modeling with Objects. Selecting Distributions. Modeling Relationships. Time Series Models. Optimization and Decision Making. Appendix A: Monte Carlo Simulation Software.
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