Computation and Modelling in Insurance and Finance, B?lviken
Автор: Musiela Marek Название: Martingale Methods in Financial Modelling ISBN: 3540209662 ISBN-13(EAN): 9783540209669 Издательство: Springer Рейтинг: Цена: 11738.00 р. 16769.00-30% Наличие на складе: Есть (1 шт.) Описание: In the 2nd edition some sections of Part I are omitted for better readability, and a brand new chapter is devoted to volatility risk. As a consequence, hedging of plain-vanilla options and valuation of exotic options are no longer limited to the Black-Scholes framework with constant volatility. The theme of stochastic volatility also reappears systematically in the second part of the book, which has been revised fundamentally, presenting much more detailed analyses of the various interest-rate models available: the authors' perspective throughout is that the choice of a model should be based on the reality of how a particular sector of the financial market functions, never neglecting to examine liquid primary and derivative assets and identifying the sources of trading risk associated. This long-awaited new edition of an outstandingly successful, well-established book, concentrating on the most pertinent and widely accepted modelling approaches, provides the reader with a text focused on practical rather than theoretical aspects of financial modelling.
Автор: Chen Ming-Hui, Shao Qi-Man, Ibrahim Joseph G. Название: Monte Carlo Methods in Bayesian Computation ISBN: 0387989358 ISBN-13(EAN): 9780387989358 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines advanced Bayesian computational methods. It presents methods for sampling from posterior distributions and discusses how to compute posterior quantities of interest using Markov chain Monte Carlo (MCMC) samples. This book examines each of these issues in detail and heavily focuses on computing various posterior quantities of interest from a given MCMC sample. Several topics are addressed, including techniques for MCMC sampling, Monte Carlo methods for estimation of posterior quantities, improving simulation accuracy, marginal posterior density estimation, estimation of normalizing constants, constrained parameter problems, highest posterior density interval calculations, computation of posterior modes, and posterior computations for proportional hazards models and Dirichlet process models. The authors also discuss computions involving model comparisons, including both nested and non-nested models, marginal likelihood methods, ratios of normalizing constants, Bayes factors, the Savage-Dickey density ratio, Stochastic Search Variable Selection, Bayesian Model Averaging, the reverse jump algorithm, and model adequacy using predictive and latent residual approaches.The book presents an equal mixture of theory and applications involving real data. The book is intended as a graduate textbook or a reference book for a one semester course at the advanced masters or Ph.D. level. It would also serve as a useful reference book for applied or theoretical researchers as well as practitioners.Ming-Hui Chen is Associate Professor of Mathematical Sciences at Worcester Polytechnic Institute, Qu-Man Shao is Assistant Professor of Mathematics at the University of Oregon. Joseph G. Ibrahim is Associate Professor of Biostatistics at the Harvard School of Public Health and Dana-Farber Cancer Institute.
Автор: Alan Genz; Frank Bretz Название: Computation of Multivariate Normal and t Probabilities ISBN: 364201688X ISBN-13(EAN): 9783642016882 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Multivariate normal and t probabilities are needed for statistical inference in many applications. This book describes the developed methods for accurate and efficient computation of the required probability values for problems with two or more variables. It discusses methods for specialized problems as well as methods for general problems.
Описание: Statistical methodology plays a key role in ensuring that DNA evidence is collected, interpreted, analyzed, and presented correctly. With the recent advances in computer technology, this methodology is more complex than ever before. There are a growing number of books in the area but none are devoted to the computational analysis of evidence.
Автор: Straub Название: Non-Life Insurance Mathematics ISBN: 3540187871 ISBN-13(EAN): 9783540187875 Издательство: Springer Рейтинг: Цена: 9357.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book gives a comprehensive overview of modern non-life actuarial science. It starts with a verbal description (i.e. without using mathematical formulae) of
the main actuarial problems to be solved in non-life practice.
Then in an extensive second chapter all the mathematical tools needed to solve these problems are dealt with -
now in mathematical notation. The rest of the book is devoted to the exact formulation of various problems and their possible solutions. Being a good mixture of practical problems and
their actuarial solutions, the book addresses above all two types of readers: firstly students (of mathematics, probability and statistics, informatics, economics) having some mathematical
knowledge, and secondly insurance practitioners who remember mathematics only from some distance.
Prerequisites are basic calculus and probability theory.
Автор: D. J. Daley Название: Epidemic Modelling ISBN: 0521014670 ISBN-13(EAN): 9780521014670 Издательство: Cambridge Academ Рейтинг: Цена: 7762.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a general introduction to the ideas and techniques required for the mathematical modelling of diseases. Exercises and complementary results extend the scope of the text, which will be useful for students of mathematical biology who have some basic knowledge of probability and statistics.
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