Author: GRG


Value at Risk, 3rd Ed.: The New Benchmark for Managing Financial Risk

[ReviewAZON asin=”0071464956″]

Since its original publication, Value at Risk has become the industry standard in risk management. Now in its Third Edition, this international bestseller addresses the fundamental changes in the field that have occurred across the globe in recent years. Philippe Jorion provides the most current information needed to understand and implement VAR-as well as manage newer dimensions of financial risk. Featured updates include:

  • An increased emphasis on operational risk
  • Using VAR for integrated risk management and to measure economic capital
  • Applications of VAR to risk budgeting in investment management
  • Discussion of new risk-management techniques, including extreme value theory, principal components, and copulas
  • Extensive coverage of the recently finalized Basel II capital adequacy rules for commercial banks, integrated throughout the book

    A major new feature of the Third Edition is the addition of short questions and exercises at the end of each chapter, making it even easier to check progress. Detailed answers are posted on the companion web site The web site contains other materials, including additional questions that course instructors can assign to their students.

    Jorion leaves no stone unturned, addressing the building blocks of VAR from computing and backtesting models to forecasting risk and correlations. He outlines the use of VAR to measure and control risk for trading, for investment management, and for enterprise-wide risk management. He also points out key pitfalls to watch out for in risk-management systems.

    The value-at-risk approach continues to improve worldwide standards for managing numerous types of risk. Now more than ever, professionals can depend on Value at Risk for comprehensive, authoritative counsel on VAR, its application, and its results-and to keep ahead of the curve.


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  • Books

    Introduction to Risk Analysis: A Systematic Approach to Science-Based Decision Making

    [ReviewAZON asin=”0865876967″]Written for safety and loss-control, environmental, and quality managers, this is the first comprehensive, integrated guide to developing a complete environmental risk analysis for regulated substances and processes. Unlike other books, Introduction to Risk Analysis looks at risk from a regulatory perspective, allowing both professionals in regulatory agencies concerned with risk_including OSHA, EPA, USDA, DOT, FDA, and state environmental agencies_and professionals in any agency-regulated industry to understand and implement the methods required for proper risk assessment.[/ReviewAZON]

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    Probability Methods for Cost Uncertainty Analysis : A Systems Engineering Perspective

    [ReviewAZON asin=”0824789660″]A careful blend of theory and practice, this book presents a comprehensive approach to assessing the impact of unplanned events on the cost of engineering complex systems. It illustrates how probability theory is applied to model, measure, and manage risk in the cost of a systems engineering project. The book contains numerous mathematical and professional anecdotes, case studies, results, observations, and interpretations that clarify the challenges in cost risk analysis. It includes references, equations, and illustrations, provides theoretical and applied exercises, and uses examples and case discussions derived from systems engineering projects to describe key concepts.[/ReviewAZON]

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    Risk Analysis: A Quantitative Guide

    [ReviewAZON asin=”0470512849″]Risk Analysis concerns itself with the quantification of risk, the modeling of identified risks and how to make decisions from those models. Quantitative risk analysis (QRA) using Monte Carlo simulation offers a powerful and precise method for dealing with the uncertainty and variability of a problem. By providing the building blocks the author guides the reader through the necessary steps to produce an accurate risk analysis model and offers general and specific techniques to cope with most modeling problems. A wide range of solved problems is used to illustrate these techniques and how they can be used together to solve otherwise complex problems.[/ReviewAZON]

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    Risk and Decision Analysis in Projects (Cases in project and program management series)

    [ReviewAZON asin=”1880410281″]Is there anything more important to the success of a project than making good decisions? This skill is certainly at or near the top of the list. Yet, few of us have had formal training in decision making. Decision analysis is the discipline that helps people choose wisely under conditions of uncertainty. This book introduces risk and decision analysis applied to project management. Probability is the language of uncertainty. Fortunately, a few basic concepts in probability and statistics go a long way toward making better decisions. The evaluation calculations are straightforward, and many everyday problems can be solved with a handheld calculator. Schuyler also explains and demystifies key concepts and techniques, including expected value, optimal decision policy, decision trees, the value of information, Monte Carlo simulation, probabilistic techniques, modeling techniques, judgments and biases, utility and multi-criteria decisions, and stochastic variance.

    Some of Schuyler’s tried-and-true tips include:

    -The single-point estimate is almost always wrong, so that it is always better to express judgments as ranges. A probability distribution completely expresses someone’s judgment about the likelihood of values within the range.

    -We often need a single-value cost or other assessment, and the expected value (mean) of the distribution is the only unbiased predictor. Expected value is the probability-weighted average, and this statistical idea is the cornerstone of decision analysis.

    -Some decisions are easy, perhaps aided by quick decision tree calculations on the back of an envelope. Decision dilemmas typically involve risky outcomes, many factors, and the best alternatives having comparable value. We only need analysis sufficient to confidently identify the best alternative. As soon as you know what to do, stop the analysis!

    -Be alert to ways to beneficially change project risks. We can often eliminate, avoid, transfer, or mitigate threats in some way. Get to know the people who make their living helping managers sidestep risk. They include insurance agents, partners, turnkey contractors, accountants, trainers, and safety personnel.[/ReviewAZON]

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    Simulation Modeling and Analysis

    [ReviewAZON asin=”0071255192″]This authoritative, comprehensive and thoroughly revised text is designed for a one term or two quarter course in simulation taught at the senior or graduate level. It is offered in departments of industrial engineering, business, computer science and operations research. New features include an innovative chapter on simulation of manufacturing systems and an up-to-date treatment of simulation software and animation, with definitive coverage of model validation, input probability distribution and analysis of simulation output data.[/ReviewAZON]

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    Simulation Modeling Using @RISK: Updated for Version 4

    [ReviewAZON asin=”053438059X”]With its understandable explanations of Monte Carlo and step-by-step instructions for Microsoft Excel, Lotus, and @Risk software, this text/software package offers both the instruction and the practice students need to begin solving complex business problems. It is designed for use as the primary learning tool in a short business simulation course (for advanced undergraduate and MBA students), or as a supplement to courses in investments, corporate finance, management science, marketing strategy, operations management, and actuarial science.[/ReviewAZON]

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    Statistical Distributions

    [ReviewAZON asin=”0471371246″]From the reviews:

    “Concise and useful summaries of the salient facts and formulas relating to [various] distributions.” -Journal of the American Statistical Association

    “A worthwhile reference.” -Journal of Quality Technology

    Since the previous edition of this popular guide to the most commonly used statistical distributions was published in 1993, statistical methods have found many new applications in science, medicine, engineering, business/finance, and the social sciences. To keep pace with these developments and to highlight the growing influence of statistical software and data management techniques, this new edition is now thoroughly updated and revised. Through clear, concise, easy-to-follow presentations, the authors discuss the key facts and formulas for 40 major probability distributions, fine-tune all existing material, and continue to offer ready access to vital information gleaned from hard-to-find places across the literature. Highly useful both as an introduction to basic principles and as a quick reference guide, Statistical Distributions, Third Edition:
    * Presents the 40 distributions in alphabetical order
    * Provides all key formulas for each distribution
    * Adds a new chapter on the Empirical Distribution Function
    * Expands the Weibull Distribution to cover the 3 and 5 parameter versions
    * Incorporates diagrams and tables illustrating the characteristics of each distribution
    * Discusses the types of application for which distributions are used
    * Features references to relevant software packages[/ReviewAZON]

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    Decisions Involving Uncertainty : An @RISK Tutorial for the Petroleum Industry

    [ReviewAZON asin=”1893281027″]A great extension of Dr. Murtha’s highly successful seminars on the use of @RISK in the petroleum industry. You start with 2 chapters to get up to speed on the philosophy of risk analysis and the requisite principles in probability, statistics, and Monte Carlo simulation. Following are the basic steps you’d take to actually build, run, and interpret results for a real risk analysis model in @RISK. To make it as hands-on as possible, Dr. Murtha includes lots of petroleum examples – an accompanying CD includes all these examples pre-built in Excel worksheets. Volumetric reserves, exponential decline, porosity and water saturation, waterflood prospect, and competitive bidding are some of the examples. This is a rare offering in that you’ll learn about the concepts of risk analysis while also getting some very solid hands-on experience with risk analysis modelling in @RISK 4.0. A trial version of @RISK 4.0 is also included![/ReviewAZON]

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