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Author: Henryk Gzyl
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110516136
Category : Mathematics
Languages : en
Pages : 235
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Book Description
This volume deals with two complementary topics. On one hand the book deals with the problem of determining the the probability distribution of a positive compound random variable, a problem which appears in the banking and insurance industries, in many areas of operational research and in reliability problems in the engineering sciences. On the other hand, the methodology proposed to solve such problems, which is based on an application of the maximum entropy method to invert the Laplace transform of the distributions, can be applied to many other problems. The book contains applications to a large variety of problems, including the problem of dependence of the sample data used to estimate empirically the Laplace transform of the random variable. Contents Introduction Frequency models Individual severity models Some detailed examples Some traditional approaches to the aggregation problem Laplace transforms and fractional moment problems The standard maximum entropy method Extensions of the method of maximum entropy Superresolution in maxentropic Laplace transform inversion Sample data dependence Disentangling frequencies and decompounding losses Computations using the maxentropic density Review of statistical procedures
Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 0470391332
Category : Business & Economics
Languages : en
Pages : 758
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Book Description
An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.
Author: Henryk Gzyl
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110516136
Category : Mathematics
Languages : en
Pages : 235
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Book Description
This volume deals with two complementary topics. On one hand the book deals with the problem of determining the the probability distribution of a positive compound random variable, a problem which appears in the banking and insurance industries, in many areas of operational research and in reliability problems in the engineering sciences. On the other hand, the methodology proposed to solve such problems, which is based on an application of the maximum entropy method to invert the Laplace transform of the distributions, can be applied to many other problems. The book contains applications to a large variety of problems, including the problem of dependence of the sample data used to estimate empirically the Laplace transform of the random variable. Contents Introduction Frequency models Individual severity models Some detailed examples Some traditional approaches to the aggregation problem Laplace transforms and fractional moment problems The standard maximum entropy method Extensions of the method of maximum entropy Superresolution in maxentropic Laplace transform inversion Sample data dependence Disentangling frequencies and decompounding losses Computations using the maxentropic density Review of statistical procedures
Author: Ellen Naylor
Publisher:
ISBN: 9780997272215
Category : Business intelligence
Languages : en
Pages : 218
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Book Description
If your company is struggling, losing its visibility or failing in growth projections, you need Win/Loss Analysis. Woven throughout are steps to gather competitive intelligence and customer insight. With the guidance of this book, you will remove the guesswork and gain more business through Win/Loss Analysis.
Author: Arthur Charpentier
Publisher: CRC Press
ISBN: 1498759823
Category : Business & Economics
Languages : en
Pages : 652
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Book Description
A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/
Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1000708039
Category : Mathematics
Languages : en
Pages : 836
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Book Description
Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Author: Bart Baesens
Publisher: John Wiley & Sons
ISBN: 1119143985
Category : Business & Economics
Languages : en
Pages : 517
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Book Description
The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided. Coverage includes data analysis and preprocessing, credit scoring; PD and LGD estimation and forecasting, low default portfolios, correlation modeling and estimation, validation, implementation of prudential regulation, stress testing of existing modeling concepts, and more, to provide a one-stop tutorial and reference for credit risk analytics. The companion website offers examples of both real and simulated credit portfolio data to help you more easily implement the concepts discussed, and the expert author team provides practical insight on this real-world intersection of finance, statistics, and analytics. SAS is the preferred software for credit risk modeling due to its functionality and ability to process large amounts of data. This book shows you how to exploit the capabilities of this high-powered package to create clean, accurate credit risk management models. Understand the general concepts of credit risk management Validate and stress-test existing models Access working examples based on both real and simulated data Learn useful code for implementing and validating models in SAS Despite the high demand for in-house models, there is little comprehensive training available; practitioners are left to comb through piece-meal resources, executive training courses, and consultancies to cobble together the information they need. This book ends the search by providing a comprehensive, focused resource backed by expert guidance. Credit Risk Analytics is the reference every risk manager needs to streamline the modeling process.
Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 1119538033
Category : Business & Economics
Languages : en
Pages : 218
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Book Description
Solutions manual to accompany a text with comprehensive coverage of actuarial modeling techniques The Student Solutions Manual to Accompany Loss Models: From Data to Decisions covers solutions related to the companion text. The manual and text are designed for use by actuaries and those studying for the profession. Readers can learn modeling techniques used across actuarial science. Knowledge of the techniques is also beneficial for those who use loss data to build models for risk assessment.
Author: Philippa X. Girling
Publisher: John Wiley & Sons
ISBN: 1118532457
Category : Business & Economics
Languages : en
Pages : 354
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Book Description
A best practices guide to all of the elements of an effective operational risk framework While many organizations know how important operational risks are, they still continue to struggle with the best ways to identify and manage them. Organizations of all sizes and in all industries need best practices for identifying and managing key operational risks, if they intend on exceling in today's dynamic environment. Operational Risk Management fills this need by providing both the new and experienced operational risk professional with all of the tools and best practices needed to implement a successful operational risk framework. It also provides real-life examples of successful methods and tools you can use while facing the cultural challenges that are prevalent in this field. Contains informative post-mortems on some of the most notorious operational risk events of our time Explores the future of operational risk in the current regulatory environment Written by a recognized global expert on operational risk An effective operational risk framework is essential for today's organizations. This book will put you in a better position to develop one and use it to identify, assess, control, and mitigate any potential risks of this nature.
Author:
Publisher:
ISBN:
Category : Continental shelf
Languages : en
Pages : 380
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Book Description
Author: Brendon Young
Publisher: John Wiley & Sons
ISBN: 0470745991
Category : Business & Economics
Languages : en
Pages : 456
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Book Description
Operational risk assessment The Commercial Imperative of a More Forensic and Transparent Approach Brendon Young and Rodney Coleman “Brendon Young and Rodney Coleman's book is extremely timely. There has never been a greater need for the financial industry to reassess the way it looks at risk. [...] They are right to draw attention to the current widespread practices of risk management, which [...] have allowed risk to become underpriced across the entire industry.” Rt Hon John McFall MP, Chairman, House of Commons Treasury Committee Failure of the financial services sector to properly understand risk was clearly demonstrated by the recent 'credit crunch'. In its 2008 Global Stability Report, the IMF sharply criticised banks and other financial institutions for the failure of risk management systems, resulting in excessive risk-taking. Financial sector supervision and regulation was also criticised for lagging behind shifts in business models and rapid innovation. This book provides investors with a sound understanding of the approaches used to assess the standing of firms and determine their true potential (identifying probable losers and potential longer-term winners). It advocates a 'more forensic' approach towards operational risk management and promotes transparency, which is seen as a facilitator of competition and efficiency as well as being a barrier to fraud, corruption and financial crime. Risk assessment is an integral part of informed decision making, influencing strategic positioning and direction. It is fundamental to a company’s performance and a key differentiator between competing management teams. Increasing complexity is resulting in the need for more dynamic, responsive approaches to the assessment and management of risk. Not all risks can be quantified; however, it remains incumbent upon management to determine the impact of possible risk-events on financial statements and to indicate the level of variation in projected figures. To begin, the book looks at traditional methods of risk assessment and shows how these have developed into the approaches currently being used. It then goes on to consider the more advanced forensic techniques being developed, which will undoubtedly increase understanding. The authors identify 'best practice' and address issues such as the importance of corporate governance, culture and ethics. Insurance as a mitigant for operational risk is also considered. Quantitative and qualitative risk assessment methodologies covered include: Loss-data analysis; extreme value theory; causal analysis including Bayesian Belief Networks; control risk self-assessment and key indicators; scenario analysis; and dynamic financial analysis. Views of industry insiders, from organisations such as Standard & Poors, Fitch, Hermes, USS, UN-PRI, Deutsche Bank, and Alchemy Partners, are presented together with those from experts at the FSA, the International Accounting Standards Board (IASB), and the Financial Reporting Council. In addition to investors, this book will be of interest to actuaries, rating agencies, regulators and legislators, as well as to the directors and risk managers of financial institutions in both the private and public sectors. Students requiring a comprehensive knowledge of operational risk management will also find the book of considerable value.
