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All property and casualty insurers are required to carry out loss reserving as a statutory accounting function. Thus, loss reserving is an essential sphere of activity, and one with its own specialized body of knowledge. While few books have been devoted to the topic, the amount of published research literature on loss reserving has almost doubled in size during the last fifteen years. Greg Taylor's book aims to provide a comprehensive, state-of-the-art treatment of loss reserving that reflects contemporary research advances to date. Divided into two parts, the book covers both the conventional techniques widely used in practice, and more specialized loss reserving techniques employing stochastic models. Part I, Deterministic Models, covers very practical issues through the abundant use of numerical examples that fully develop the techniques under consideration. Part II, Stochastic Models, begins with a chapter that sets up the additional theoretical material needed to illustrate stochastic modeling. The remaining chapters in Part II are self-contained, and thus can be approached independently of each other. A special feature of the book is the use throughout of a single real life data set to illustrate the numerical examples and new techniques presented. The data set illustrates most of the difficult situations presented in actuarial practice. This book will meet the needs for a reference work as well as for a textbook on loss reserving.

Actuarial mathematics --- Insurance --- Reserves --- Business. --- Management science. --- Finance. --- Business and Management, general. --- Finance, general. --- Funding --- Funds --- Economics --- Currency question --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Trade --- Commerce --- Industrial management --- Insurance - Reserves

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In "Simulating Society", the authors explore the basis for social and economic behavior. Using the methodology of computer simulation, specifically cellular automata, they model various factors that are involved in a system of individuals (or agents) who interact socially and economically with one another. The usefulness of computer simulations in the social sciences is that it provides a laboratory in which qualitative ideas about social and economic interactions can be tested. This brings a new dimension to the social sciences where 'explanations' abound, but are rarely subject to much experimental testing. Mathematica is used as the programming language for implementing these models as cellular automata simulations. The authors have chosen this language because it has a number of features which make it uniquely qualified to be used by social scientists, especially those without expertise in computer programming. Users can easily access the various 3.0 Mathematica notebooks, and readily interact with them, the full text of the printed book, itself, and other data contained on www.telospub.com.

Quantitative methods in social research --- Economics. --- Social interaction --- Socialization --- Sociology & Social History --- Social Sciences --- Social Change --- Computer simulation --- Economic theory. --- Business. --- Management science. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Business and Management, general. --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Trade --- Economics --- Commerce --- Industrial management --- Economic theory --- Political economy --- Social sciences --- Economic man --- Computer simulation. --- Mathematica (Computer file) --- Human interaction --- Interaction, Social --- Symbolic interaction --- Exchange theory (Sociology) --- Psychology --- Social psychology --- Child socialization --- Children --- Enculturation --- Social education --- Education --- Sociology

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This book is different from all other books on Life Insurance by at least one of the following characteristics 1-4. 1. The treatment of life insurances at three different levels: time-capital, present value and price level. We call time-capital any distribution of a capital over time: (*) is the time-capital with amounts Cl, ~, ... , C at moments Tl, T , ..• , T resp. N 2 N For instance, let (x) be a life at instant 0 with future lifetime X. Then the whole oO oO life insurance A is the time-capital (I,X). The whole life annuity ä is the x x time-capital (1,0) + (1,1) + (1,2) + ... + (I,'X), where 'X is the integer part ofX. The present value at 0 of time-capital (*) is the random variable T1 T TN Cl V + ~ v , + ... + CNV . (**) In particular, the present value ofA 00 and ä 00 is x x 0 0 2 A = ~ and ä = 1 + v + v + ... + v'X resp. x x The price (or premium) of a time-capital is the expectation of its present value. In particular, the price ofA 00 and äx 00 is x 2 A = E(~) and ä = E(I + v + v + ... + v'X) resp.

Actuarial mathematics --- Life insurance --- Assurance-vie --- Mathematics --- Mathématiques --- Insurance, life --- Mathematics. --- 368.30 --- Insurance, Life --- -10.03.a --- Insurance --- Viatical settlements --- Levensverzekering --- Actuariaat ; Algemeen --- 368.30 Levensverzekering --- Mathématiques --- 10.03.a --- Actuarial science. --- Business. --- Management science. --- Finance. --- Economic theory. --- Actuarial Sciences. --- Business and Management, general. --- Finance, general. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Economic theory --- Political economy --- Social sciences --- Economic man --- Funding --- Funds --- Economics --- Currency question --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Trade --- Commerce --- Industrial management --- Statistics --- Insurance, life - Mathematics.

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Modeling is a tool used by savvy business managers to understand the processes of their businesses and to estimate the impact of changes. Dynamic Modeling for Business Management demonstrates dynamic modeling techniques beginning with fundamental processes and advancing to more complex business models. Discussions of modeling emphasize its practical use for decision-making and in implementing change for measurable results. Readers will learn both manufacturing and service-oriented business processes through hands-on lessons. They will then be able to manipulate additional models to test their knowledge and address issues specific to their own businesses and interests. Some of the topics covered include workflow management, supply-chain management, and business strategy.

Management --- Digital computer simulation. --- Mathematical models. --- Programming --- Organization theory --- Mathematics. --- Business. --- Management science. --- Management. --- Applied mathematics. --- Engineering mathematics. --- Industrial organization. --- Economics. --- Applications of Mathematics. --- Business and Management, general. --- Economic Systems. --- Industrial Organization. --- Political Economy/Economic Systems. --- Economic policy. --- Administration --- Industrial relations --- Organization --- Industries --- Industrial concentration --- Industrial management --- Industrial sociology --- Economic theory --- Political economy --- Social sciences --- Economic man --- Economic nationalism --- Economic planning --- National planning --- State planning --- Economics --- Planning --- National security --- Social policy --- Quantitative business analysis --- Problem solving --- Operations research --- Statistical decision --- Trade --- Commerce --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics

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Randall B, Lowe Piper & Marbury, L.L.R The issue of costing and pricing in the telecommunications industry has been hotly debated for the last twenty years. Indeed, we are still wrestling today over the cost of the local exchange for access by interexchange and competitive local ex­ change carriers, as well as for universal service funding. The U.S. telecommunications world was a simple one before the emergence of competition, comprising only AT&T and independent local exchange carriers. Costs were allocated between intrastate and interstate jurisdictions and then again, between intrastate local and toll. The Bell System then divided those costs among itself (using a process referred to as the division of revenues) and independents (using a process called settlements). Tolls subsidized local calls to keep the politi­ cians happy, and the firm, as a whole, covered its costs and made a fair return. State regulators, however, lacked the wherewithal to audit this process. Their con­ cerns centered generally on whether local rates, irrespective of costs, were at a po­ litically acceptable level. Although federal regulators were better able to determine the reasonableness of the process and the resulting costs, they adopted an approach of "continuous surveillance" where, like the state regulator, the appearance of rea­ sonableness was what mattered. With the advent of competition, this historical costing predicate had to change. The Bell System, as well as the independents, were suddenly held accountable.

Telecommunication services --- Capital structure --- Real options (Finance) --- Options réelles (Finances) --- Coût --- Capital budget. --- Telecommunication -- Economic aspects. --- Business. --- Management science. --- Information technology. --- Business --- Industrial organization. --- Economics. --- Industrial Organization. --- Business and Management, general. --- IT in Business. --- Data processing. --- Telecommunication --- Options (Finance) --- Economic aspects. --- Options (Finance). --- Business—Data processing. --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Trade --- Economics --- Commerce --- Industrial management --- Industries --- Organization --- Industrial concentration --- Industrial sociology --- Capital assets pricing model. --- Investments --- Mathematical models. --- Capital asset pricing model --- CAPM (Capital assets pricing model) --- Pricing model, Capital assets --- Capital --- Finance --- Mathematical models