Practical Spreadsheet Risk Modeling For Management

This book offers a one-stop resource for performing quantitative risk analyses. The authors provide practical case studies along with detailed instruction and illustration of the features of ModelRisk, the most advanced risk modeling spreadsheet software currently available. The specific examples in the text demonstrate a number of cutting-edge tools and techniques that are very powerful in risk analysis but that are not available in other spreadsheet simulation programs. The book covers modeling complex correlations, aggregating uncertainty and variability, and estimating parameter and model uncertainty. The included CD-ROM provides a 120-day trial of ModelRisk.

Practical Spreadsheet Modeling Using @Risk provides a guide of how to construct applied decision analysis models in spreadsheets. The focus is on the use of Monte Carlo simulation to provide quantitative assessment of uncertainties and key risk drivers. The book presents numerous examples based on real data and relevant practical decisions in a variety of settings, including health care, transportation, finance, natural resources, technology, manufacturing, retail, and sports and entertainment. All examples involve decision problems where uncertainties make simulation modeling useful to obtain decision insights and explore alternative choices. Good spreadsheet modeling practices are highlighted. The book is suitable for graduate students or advanced undergraduates in business, public policy, health care administration, or any field amenable to simulation modeling of decision problems. The book is also useful for applied practitioners seeking to build or enhance their spreadsheet modeling skills. Features Step-by-step examples of spreadsheet modeling and risk analysis in a variety of fields Description of probabilistic methods, their theoretical foundations, and their practical application in a spreadsheet environment Extensive example models and exercises based on real data and relevant decision problems Comprehensive use of the @Risk software for simulation analysis, including a free one-year educational software license

Practical Spreadsheet Modeling Using @Risk provides a guide of how to construct applied decision analysis models in spreadsheets. The focus is on the use of Monte Carlo simulation to provide quantitative assessment of uncertainties and key risk drivers. The book presents numerous examples based on real data and relevant practical decisions in a variety of settings, including health care, transportation, finance, natural resources, technology, manufacturing, retail, and sports and entertainment. All examples involve decision problems where uncertainties make simulation modeling useful to obtain decision insights and explore alternative choices. Good spreadsheet modeling practices are highlighted. The book is suitable for graduate students or advanced undergraduates in business, public policy, health care administration, or any field amenable to simulation modeling of decision problems. The book is also useful for applied practitioners seeking to build or enhance their spreadsheet modeling skills. Features Step-by-step examples of spreadsheet modeling and risk analysis in a variety of fields Description of probabilistic methods, their theoretical foundations, and their practical application in a spreadsheet environment Extensive example models and exercises based on real data and relevant decision problems Comprehensive use of the @Risk software for simulation analysis, including a free one-year educational software license

CD-ROM contains: Crystal Ball 2000 2 Professional Student Edition; ProblemSolver for Education v.5, Tree Plan vl 64 and maunal, and data files for examples, cases and projects.

Named peril index insurance has great potential to address unmet risk management needs for agricultural insurance in developing economies, potentially contributing to increased agricultural sustainability and improved food security. However, the development and appraisal of index insurance business lines is not without challenges. Insurers must rigorously evaluate the quality of the products they offer and take care to ensure that distributors and policyholders understand the benefits and limits of the purchased coverage. Without these important steps to ensure responsible insurance practices, insurers can damage the implementation and potential of index insurance in the market. Risk Modeling for Appraising Named Peril Index Insurance Products: A Guide for Practitioners helps stakeholders in the named peril index insurance industry appraise new and existing products. Part 1 of the guide provides a summary of the insights and decisions required for the insurer to make an informed decision to launch and expand an index insurance business line. Insurance managers are the primary audience for part 1. Part 2 provides a step-by-step guide to calculating the decision metrics used by the insurance manager in part 1. These metrics are calculated using probabilistic modeling that provides insights into risks related to the index insurance product. Actuarial analysts are the primary audience for part 2. In an increasingly competitive insurance market, creative product development and imaginative business strategies are becoming the norm. This guide will help emerging market insurers who seek to stay on the cutting edge to successfully and sustainably penetrate new market segments.

In today's increasingly competitive financial world, successful risk management, portfolio management, and financial structuring demand more than up-to-date financial know-how. They also call for quantitative expertise, including the ability to effectively apply mathematical modeling tools and techniques, in this case credit. Credit Risk Modeling using Excel and VBA with DVD provides practitioners with a hands on introduction to credit risk modeling. Instead of just presenting analytical methods it shows how to implement them using Excel and VBA, in addition to a detailed description in the text a DVD guides readers step by step through the implementation. The authors begin by showing how to use option theoretic and statistical models to estimate a borrowers default risk. The second half of the book is devoted to credit portfolio risk. The authors guide readers through the implementation of a credit risk model, show how portfolio models can be validated or used to access structured credit products like CDO’s. The final chapters address modeling issues associated with the new Basel Accord.

This volume shows how spreadsheets are used in real life to model and analyse real business problems. By modelling problems using spreadsheets from the outset the text prepares future managers for the types of problems they will encounter in their daily workload.

Risk modeling is now a core skill for successful managers inside and outside finance. Alastair Day's "Mastering Risk Modelling" shows managers exactly how to build Excel-based models for identifying, quantifying and managing risk--models that provide clear, accurate decision-making guidance that can be used with confidence throughout the enterprise. An ideal follow-up to Day's bestselling "Mastering Financial Modelling," the book brings together risk modeling theory and practice more effectively than ever before. Day presents extensive tips and methods for developing Excel-based risk applications--including practical guidance on designing models and layering complexity on top of basic models. His series of Excel templates will jumpstart your own modeling, eliminate the need to start from scratch, and provide powerful insights for improving any model. All models are provided on an accompanying CD-ROM.