Download or read book Practical Spreadsheet Risk Modeling Using Risk written by Dale Lehman and published by CRC Press. This book was released on 2019-11-29 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Practical Spreadsheet Modeling Using Risk written by Dale Lehman and published by CRC Press. This book was released on 2019-11-11 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Practical Spreadsheet Risk Modeling for Management written by Dale Lehman and published by CRC Press. This book was released on 2016-04-19 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Credit Risk Modeling using Excel and VBA written by Gunter Löeffler and published by John Wiley & Sons. This book was released on 2011-01-31 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is common to blame the inadequacy of credit risk models for the fact that the financial crisis has caught many market participants by surprise. On closer inspection, though, it often appears that market participants failed to understand or to use the models correctly. The recent events therefore do not invalidate traditional credit risk modeling as described in the first edition of the book. A second edition is timely, however, because the first dealt relatively briefly with instruments featuring prominently in the crisis (CDSs and CDOs). In addition to expanding the coverage of these instruments, the book will focus on modeling aspects which were of particular relevance in the financial crisis (e.g. estimation error) and demonstrate the usefulness of credit risk modelling through case studies. This book provides practitioners and students with an intuitive, hands-on introduction to modern credit risk modelling. Every chapter starts with an explanation of the methodology and then the authors take the reader step by step through the implementation of the methods in Excel and VBA. They focus specifically on risk management issues and cover default probability estimation (scoring, structural models, and transition matrices), correlation and portfolio analysis, validation, as well as credit default swaps and structured finance. The book has an accompanying website, https://creditriskmodeling.wordpress.com/, which has been specially updated for this Second Edition and contains slides and exercises for lecturers.
Download or read book Practical Risk Analysis for Project Planning written by Galit Shmueli and published by Axelrod Schnall Publishers. This book was released on 2016-07-14 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Projects are investments of resources for achieving a particular objective or set of objectives. Resources include time, money, manpower, and sometimes lives. Objectives include financial gain, social and health benefits, national goals, educational and scientific achievements, and reduction of suffering, among many others. Projects are undertaken by large and small organizations, by governments, non-profit organizations, private businesses, and by individuals. Determining whether to execute a project, or which project to execute among a set of possibilities is often a challenge with high stakes. Assessing the potential outcomes of a project can therefore be detrimental, leading to the importance of making informative decisions. Practical Risk Analysis for Project Planning is a hands-on introduction to integrating numerical data and domain knowledge into popular spreadsheet software such as Microsoft Excel or Google Spreadsheets, to arrive at informed project-planning decisions. The focus of the book is on formalizing domain expertise into numerical data, providing tools for assessing potential project performance, and evaluating performance under realistic uncertainty. The book introduces basic principles for assessing potential project performance and risk under different scenarios, by addressing uncertainty that arises at different levels. It describes measures of expected performance and risk, presents approaches such as scenario building and Monte Carlo simulation for addressing uncertainty, and introduces methods for comparing competing projects and reducing risk via project portfolios. No special software is required except Excel or another spreadsheet software. While the book assumes no knowledge of statistics, operations research, or management science, it does rely on basic familiarity with Excel. Chapter exercises and examples of real projects are aimed at hands-on learning. For more information visit RiskAnalysisBook.com
Download or read book Credit Risk Modeling using Excel and VBA written by Gunter Löeffler and published by Wiley. This book was released on 2007-06-05 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Mastering Risk Modelling written by Alastair L. Day and published by . This book was released on 2008 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mastering Risk Modelling written by Alastair L. Day and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains useful tips and methods for developing simple Excel applications. In particular, it discusses model design and how to layer complexity on to basic models. The result is a series of examples and building blocks for the reader to use.
Download or read book Mastering Risk Modelling written by Alastair L. Day and published by Financial Times/Prentice Hall. This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Mastering Risk Modelling' provides useful tips and methods for developing simple Excel applications. In particular, it discusses model design and how to layer complexity on to basic models. The result is a series of templates and building blocks for the reader to use.
Download or read book Risk Modeling Assessment and Management written by Yacov Y. Haimes and published by John Wiley & Sons. This book was released on 2005-02-04 with total page 862 pages. Available in PDF, EPUB and Kindle. Book excerpt: An updated and timely new look at the theory and practice of risk management Since the first edition of Risk Modeling, Assessment, and Management was published, public interest in the field of risk analysis has grown astronomically. Its adaptation across many disciplines and its deployment by industry and government agencies in decision making has led to an unprecedented development of new theory, methodology, and practical tools. The Second Edition of this well-regarded reference describes the state of the art of risk management and its important applications in such areas as engineering, science, manufacturing, business, management, and public policy. The author strikes a balance between the quantitative and the qualitative aspects of risk management, showing clearly how to quantify risk and construct probability in conjunction with real-world decision-making problems. At the same time, he addresses a host of institutional, organizational, political, and cultural considerations. Incorporating real-world examples and case studies to illustrate the analytical methods under discussion, the book presents basic concepts as well as advanced material, avoiding higher mathematics whenever possible. Some key revisions to the Second Edition include: * A completely updated format with many new examples and problems * A new chapter on Risks of Terrorism, including case studies in transportation, water supply, infrastructure interdependencies, food safety, and a National Research Council report on terrorism * A new chapter on Risk Filtering, Ranking, and Management (RFRM), a technology co-developed by the author and supported by several case studies and examples * A new focus on minimizing the high cost associated with today's more extensive risk management Examining timely, multidisciplinary practical applications, this new edition offers an important resource for industry professionals as well as advanced graduate students in systems engineering.
Download or read book Operational Risk Modeling in Financial Services written by Patrick Naim and published by John Wiley & Sons. This book was released on 2019-05-28 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform your approach to oprisk modelling with a proven, non-statistical methodology Operational Risk Modeling in Financial Services provides risk professionals with a forward-looking approach to risk modelling, based on structured management judgement over obsolete statistical methods. Proven over a decade’s use in significant banks and financial services firms in Europe and the US, the Exposure, Occurrence, Impact (XOI) method of operational risk modelling played an instrumental role in reshaping their oprisk modelling approaches; in this book, the expert team that developed this methodology offers practical, in-depth guidance on XOI use and applications for a variety of major risks. The Basel Committee has dismissed statistical approaches to risk modelling, leaving regulators and practitioners searching for the next generation of oprisk quantification. The XOI method is ideally suited to fulfil this need, as a calculated, coordinated, consistent approach designed to bridge the gap between risk quantification and risk management. This book details the XOI framework and provides essential guidance for practitioners looking to change the oprisk modelling paradigm. Survey the range of current practices in operational risk analysis and modelling Track recent regulatory trends including capital modelling, stress testing and more Understand the XOI oprisk modelling method, and transition away from statistical approaches Apply XOI to major operational risks, such as disasters, fraud, conduct, legal and cyber risk The financial services industry is in dire need of a new standard — a proven, transformational approach to operational risk that eliminates or mitigates the common issues with traditional approaches. Operational Risk Modeling in Financial Services provides practical, real-world guidance toward a more reliable methodology, shifting the conversation toward the future with a new kind of oprisk modelling.
Download or read book Business Risk and Simulation Modelling in Practice written by Michael Rees and published by John Wiley & Sons. This book was released on 2015-08-05 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complete guide to the principles and practice of risk quantification for business applications. The assessment and quantification of risk provide an indispensable part of robust decision-making; to be effective, many professionals need a firm grasp of both the fundamental concepts and of the tools of the trade. Business Risk and Simulation Modelling in Practice is a comprehensive, in–depth, and practical guide that aims to help business risk managers, modelling analysts and general management to understand, conduct and use quantitative risk assessment and uncertainty modelling in their own situations. Key content areas include: Detailed descriptions of risk assessment processes, their objectives and uses, possible approaches to risk quantification, and their associated decision-benefits and organisational challenges. Principles and techniques in the design of risk models, including the similarities and differences with traditional financial models, and the enhancements that risk modelling can provide. In depth coverage of the principles and concepts in simulation methods, the statistical measurement of risk, the use and selection of probability distributions, the creation of dependency relationships, the alignment of risk modelling activities with general risk assessment processes, and a range of Excel modelling techniques. The implementation of simulation techniques using both Excel/VBA macros and the @RISK Excel add-in. Each platform may be appropriate depending on the context, whereas the core modelling concepts and risk assessment contexts are largely the same in each case. Some additional features and key benefits of using @RISK are also covered. Business Risk and Simulation Modelling in Practice reflects the author′s many years in training and consultancy in these areas. It provides clear and complete guidance, enhanced with an expert perspective. It uses approximately one hundred practical and real-life models to demonstrate all key concepts and techniques; these are accessible on the companion website.
Download or read book Market Risk Analysis Value at Risk Models written by Carol Alexander and published by John Wiley & Sons. This book was released on 2009-02-09 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading market risk academic, Professor Carol Alexander, Value-at-Risk Models forms part four of the Market Risk Analysis four volume set. Building on the three previous volumes this book provides by far the most comprehensive, rigorous and detailed treatment of market VaR models. It rests on the basic knowledge of financial mathematics and statistics gained from Volume I, of factor models, principal component analysis, statistical models of volatility and correlation and copulas from Volume II and, from Volume III, knowledge of pricing and hedging financial instruments and of mapping portfolios of similar instruments to risk factors. A unifying characteristic of the series is the pedagogical approach to practical examples that are relevant to market risk analysis in practice. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM . Empirical examples and case studies specific to this volume include: Parametric linear value at risk (VaR)models: normal, Student t and normal mixture and their expected tail loss (ETL); New formulae for VaR based on autocorrelated returns; Historical simulation VaR models: how to scale historical VaR and volatility adjusted historical VaR; Monte Carlo simulation VaR models based on multivariate normal and Student t distributions, and based on copulas; Examples and case studies of numerous applications to interest rate sensitive, equity, commodity and international portfolios; Decomposition of systematic VaR of large portfolios into standard alone and marginal VaR components; Backtesting and the assessment of risk model risk; Hypothetical factor push and historical stress tests, and stress testing based on VaR and ETL.
Download or read book Simulation Modeling Using Risk written by Wayne L. Winston and published by . This book was released on 1996 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Risk Modeling for Appraising Named Peril Index Insurance Products written by Shadreck Mapfumo and published by World Bank Publications. This book was released on 2017-04-13 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Market Risk Analysis Practical Financial Econometrics written by Carol Alexander and published by John Wiley & Sons. This book was released on 2008-05-27 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical and selective exposition, emphasising the areas of econometrics, such as GARCH, cointegration and copulas that are required for resolving problems in market risk analysis. The book covers material for a one-semester graduate course in applied financial econometrics in a very pedagogical fashion as each time a concept is introduced an empirical example is given, and whenever possible this is illustrated with an Excel spreadsheet. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM. Empirical examples and case studies specific to this volume include: Factor analysis with orthogonal regressions and using principal component factors; Estimation of symmetric and asymmetric, normal and Student t GARCH and E-GARCH parameters; Normal, Student t, Gumbel, Clayton, normal mixture copula densities, and simulations from these copulas with application to VaR and portfolio optimization; Principal component analysis of yield curves with applications to portfolio immunization and asset/liability management; Simulation of normal mixture and Markov switching GARCH returns; Cointegration based index tracking and pairs trading, with error correction and impulse response modelling; Markov switching regression models (Eviews code); GARCH term structure forecasting with volatility targeting; Non-linear quantile regressions with applications to hedging.
Download or read book Market Risk Analysis Boxset written by Carol Alexander and published by John Wiley & Sons. This book was released on 2009-02-24 with total page 1691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Market Risk Analysis is the most comprehensive, rigorous and detailed resource available on market risk analysis. Written as a series of four interlinked volumes each title is self-contained, although numerous cross-references to other volumes enable readers to obtain further background knowledge and information about financial applications. Volume I: Quantitative Methods in Finance covers the essential mathematical and financial background for subsequent volumes. Although many readers will already be familiar with this material, few competing texts contain such a complete and pedagogical exposition of all the basic quantitative concepts required for market risk analysis. There are six comprehensive chapters covering all the calculus, linear algebra, probability and statistics, numerical methods and portfolio mathematics that are necessary for market risk analysis. This is an ideal background text for a Masters course in finance. Volume II: Practical Financial Econometrics provides a detailed understanding of financial econometrics, with applications to asset pricing and fund management as well as to market risk analysis. It covers equity factor models, including a detailed analysis of the Barra model and tracking error, principal component analysis, volatility and correlation, GARCH, cointegration, copulas, Markov switching, quantile regression, discrete choice models, non-linear regression, forecasting and model evaluation. Volume III: Pricing, Hedging and Trading Financial Instruments has five very long chapters on the pricing, hedging and trading of bonds and swaps, futures and forwards, options and volatility as well detailed descriptions of mapping portfolios of these financial instruments to their risk factors. There are numerous examples, all coded in interactive Excel spreadsheets, including many pricing formulae for exotic options but excluding the calibration of stochastic volatility models, for which Matlab code is provided. The chapters on options and volatility together constitute 50% of the book, the slightly longer chapter on volatility concentrating on the dynamic properties the two volatility surfaces the implied and the local volatility surfaces that accompany an option pricing model, with particular reference to hedging. Volume IV: Value at Risk Models builds on the three previous volumes to provide by far the most comprehensive and detailed treatment of market VaR models that is currently available in any textbook. The exposition starts at an elementary level but, as in all the other volumes, the pedagogical approach accompanied by numerous interactive Excel spreadsheets allows readers to experience the application of parametric linear, historical simulation and Monte Carlo VaR models to increasingly complex portfolios. Starting with simple positions, after a few chapters we apply value-at-risk models to interest rate sensitive portfolios, large international securities portfolios, commodity futures, path dependent options and much else. This rigorous treatment includes many new results and applications to regulatory and economic capital allocation, measurement of VaR model risk and stress testing.
