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Loss Models

Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 1118573749
Size: 14.59 MB
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An essential resource for constructing and analyzing advancedactuarial models Loss Models: Further Topics presents extended coverage ofmodeling through the use of tools related to risk theory, lossdistributions, and survival models. The book uses these methods toconstruct and evaluate actuarial models in the fields of insuranceand business. Providing an advanced study of actuarial methods, thebook features extended discussions of risk modeling and riskmeasures, including Tail-Value-at-Risk. Loss Models: FurtherTopics contains additional material to accompany the FourthEdition of Loss Models: From Data to Decisions, such as: Extreme value distributions Coxian and related distributions Mixed Erlang distributions Computational and analytical methods for aggregate claimmodels Counting processes Compound distributions with time-dependent claim amounts Copula models Continuous time ruin models Interpolation and smoothing The book is an essential reference for practicing actuaries andactuarial researchers who want to go beyond the material requiredfor actuarial qualification. Loss Models: Further Topics isalso an excellent resource for graduate students in the actuarialfield.

Reinsurance

Author: Hansjöerg Albrecher
Publisher: John Wiley & Sons
ISBN: 0470772689
Size: 37.76 MB
Format: PDF, Mobi
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Presents a comprehensive treatment of the increasingly topical field of reinsurance Reinsurance: Actuarial and Statistical Aspects provides a survey of both the academic literature in the field as well as challenges appearing in reinsurance practice and puts the two in perspective. The book is written for researchers with an interest in reinsurance problems, for graduate students with a basic knowledge of probability and statistics as well as for reinsurance practitioners. The focus of the book is on modelling together with the statistical challenges that go along with it. The discussed statistical approaches are illustrated alongside six case studies of insurance loss data sets, ranging from MTPL over fire to storm and flood loss data. Some of the presented material also contains new results that have not yet been published in the research literature. An extensive bibliography provides readers with links for further study.

Time Series Analysis

Author: Wilfredo Palma
Publisher: John Wiley & Sons
ISBN: 1118634322
Size: 21.45 MB
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A modern and accessible guide to the analysis of introductory time series data Featuring an organized and self-contained guide, Time Series Analysis provides a broad introduction to the most fundamental methodologies and techniques of time series analysis. The book focuses on the treatment of univariate time series by illustrating a number of well-known models such as ARMA and ARIMA. Providing contemporary coverage, the book features several useful and newly-developed techniques such as weak and strong dependence, Bayesian methods, non-Gaussian data, local stationarity, missing values and outliers, and threshold models. Time Series Analysis includes practical applications of time series methods throughout, as well as: Real-world examples and exercise sets that allow readers to practice the presented methods and techniques Numerous detailed analyses of computational aspects related to the implementation of methodologies including algorithm efficiency, arithmetic complexity, and process time End-of-chapter proposed problems and bibliographical notes to deepen readers’ knowledge of the presented material Appendices that contain details on fundamental concepts and select solutions of the problems implemented throughout A companion website with additional data files and computer codes Time Series Analysis is an excellent textbook for undergraduate and beginning graduate-level courses in time series as well as a supplement for students in advanced statistics, mathematics, economics, finance, engineering, and physics. The book is also a useful reference for researchers and practitioners in time series analysis, econometrics, and finance. Wilfredo Palma, PhD, is Professor of Statistics in the Department of Statistics at Pontificia Universidad Católica de Chile. Dr. Palma has published several refereed articles and has received over a dozen academic honors and awards. His research interests include time series analysis, prediction theory, state space systems, linear models, and econometrics. He is the author of Long-Memory Time Series: Theory and Methods, also published by Wiley.

Spatial And Spatio Temporal Geostatistical Modeling And Kriging

Author: José-María Montero
Publisher: John Wiley & Sons
ISBN: 1118762436
Size: 71.46 MB
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Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. The most innovative developments in the different steps of the kriging process. An up-to-date account of strategies for dealing with data evolving in space and time. An accompanying website featuring R code and examples

Student Solutions Manual To Accompany Loss Models From Data To Decisions Fourth Edition

Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 1118472020
Size: 52.51 MB
Format: PDF, ePub
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Student Solutions Manual to Accompany Loss Models: From Data to Decisions, Fourth Edition. This volume is organised around the principle that much of actuarial science consists of the construction and analysis of mathematical models which describe the process by which funds flow into and out of an insurance system.

Loss Distributions

Author: Robert V. Hogg
Publisher: John Wiley & Sons
ISBN: 0470317302
Size: 26.71 MB
Format: PDF
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Devoted to the problem of fitting parametric probability distributions to data, this treatment uniquely unifies loss modeling in one book. Data sets used are related to the insurance industry, but can be applied to other distributions. Emphasis is on the distribution of single losses related to claims made against various types of insurance policies. Includes five sets of insurance data as examples.

Loss Models From Data To Decisions 3rd Edition One Year Online

Author: Stuart A. Klugman
Publisher: Wiley
ISBN: 9781118210284
Size: 80.46 MB
Format: PDF, ePub, Docs
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"eKlugman" "ExamPrep" is an exciting new online product designed to help actuaries improve their examination skills. "eKlugman" "ExamPrep" provides an interactive method for working most of the exercises in "Loss Models" including, as well as providing, hints and step-by-step solutions. Many of the questions have a feature that makes random changes so that the same question can be worked more than once. The questions cover simulations, log normal distributions, aggregate loss models and operational risks, among a host of other actuarial topics. "eKlugman" "ExamPrep" also includes multiple forms of simulated exams with questions specially written for exam C/4 practice. The product features a built-in record keeping system in order to reinforce further practice and promote customization of study skills. This online product presents useful tips in understanding the test material, and it aids users in achieving specific exam goals. The material is a 'must have' for all aspiring and practicing actuaries who desire a fast and efficient alternative to using the traditional coursebook approach. Price includes 6-month access/subscription. Once purchased, the product is nonreturnable. After ordering, customers will be mailed a card that contains their registration code which is needed to access the "eKlugman ExamPrep" website. Also, check out the NEW enhanced version, Loss Models Online 3e. This product serves the same needs as ExamPrep, but with updated content and enhanced functionality to further improve your knowledge when preparing the the Actuarial Exam.

Operational Risk

Author: Harry H. Panjer
Publisher: John Wiley & Sons
ISBN: 0470051302
Size: 76.12 MB
Format: PDF, Kindle
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Discover how to optimize business strategies from both qualitative and quantitative points of view Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors. Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts. Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science. In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features: * Ample exercises to further elucidate the concepts in the text * Definitive coverage of distribution functions and related concepts * Models for the size of losses * Models for frequency of loss * Aggregate loss modeling * Extreme value modeling * Dependency modeling using copulas * Statistical methods in model selection and calibration Assuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also useful as a reference for practitioners in both enterprise risk management and risk and operational management.

Contemporary Bayesian Econometrics And Statistics

Author: John Geweke
Publisher: John Wiley & Sons
ISBN: 0471744727
Size: 29.26 MB
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Tools to improve decision making in an imperfect world This publication provides readers with a thorough understanding ofBayesian analysis that is grounded in the theory of inference andoptimal decision making. Contemporary Bayesian Econometrics andStatistics provides readers with state-of-the-art simulationmethods and models that are used to solve complex real-worldproblems. Armed with a strong foundation in both theory andpractical problem-solving tools, readers discover how to optimizedecision making when faced with problems that involve limited orimperfect data. The book begins by examining the theoretical and mathematicalfoundations of Bayesian statistics to help readers understand howand why it is used in problem solving. The author then describeshow modern simulation methods make Bayesian approaches practicalusing widely available mathematical applications software. Inaddition, the author details how models can be applied to specificproblems, including: * Linear models and policy choices * Modeling with latent variables and missing data * Time series models and prediction * Comparison and evaluation of models The publication has been developed and fine- tuned through a decadeof classroom experience, and readers will find the author'sapproach very engaging and accessible. There are nearly 200examples and exercises to help readers see how effective use ofBayesian statistics enables them to make optimal decisions. MATLAB?and R computer programs are integrated throughout the book. Anaccompanying Web site provides readers with computer code for manyexamples and datasets. This publication is tailored for research professionals who useeconometrics and similar statistical methods in their work. Withits emphasis on practical problem solving and extensive use ofexamples and exercises, this is also an excellent textbook forgraduate-level students in a broad range of fields, includingeconomics, statistics, the social sciences, business, and publicpolicy.

Statistical Size Distributions In Economics And Actuarial Sciences

Author: Christian Kleiber
Publisher: John Wiley & Sons
ISBN: 9780471457169
Size: 25.41 MB
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A comprehensive account of economic size distributions around theworld and throughout the years In the course of the past 100 years, economists and appliedstatisticians have developed a remarkably diverse variety of incomedistribution models, yet no single resource convincingly accountsfor all of these models, analyzing their strengths and weaknesses,similarities and differences. Statistical Size Distributions inEconomics and Actuarial Sciences is the first collection tosystematically investigate a wide variety of parametric models thatdeal with income, wealth, and related notions. Christian Kleiber and Samuel Kotz survey, compliment, compare,and unify all of the disparate models of income distribution,highlighting at times a lack of coordination between them that canresult in unnecessary duplication. Considering models from eightlanguages and all continents, the authors discuss the social andeconomic implications of each as well as distributions of size ofloss in actuarial applications. Specific models coveredinclude: Pareto distributions Lognormal distributions Gamma-type size distributions Beta-type size distributions Miscellaneous size distributions Three appendices provide brief biographies of some of theleading players along with the basic properties of each of thedistributions. Actuaries, economists, market researchers, socialscientists, and physicists interested in econophysics will findStatistical Size Distributions in Economics and Actuarial Sciencesto be a truly one-of-a-kind addition to the professionalliterature.