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Author: Yasutaka Shimizu Publisher: Springer Nature ISBN: 981169284X Category : Business & Economics Languages : en Pages : 119
Book Description
This book begins with the fundamental large sample theory, estimating ruin probability, and ends by dealing with the latest issues of estimating the Gerber–Shiu function. This book is the first to introduce the recent development of statistical methodologies in risk theory (ruin theory) as well as their mathematical validities. Asymptotic theory of parametric and nonparametric inference for the ruin-related quantities is discussed under the setting of not only classical compound Poisson risk processes (Cramér–Lundberg model) but also more general Lévy insurance risk processes. The recent development of risk theory can deal with many kinds of ruin-related quantities: the probability of ruin as well as Gerber–Shiu’s discounted penalty function, both of which are useful in insurance risk management and in financial credit risk analysis. In those areas, the common stochastic models are used in the context of the structural approach of companies’ default. So far, the probabilistic point of view has been the main concern for academic researchers. However, this book emphasizes the statistical point of view because identifying the risk model is always necessary and is crucial in the final step of practical risk management.
Author: Yasutaka Shimizu Publisher: Springer Nature ISBN: 981169284X Category : Business & Economics Languages : en Pages : 119
Book Description
This book begins with the fundamental large sample theory, estimating ruin probability, and ends by dealing with the latest issues of estimating the Gerber–Shiu function. This book is the first to introduce the recent development of statistical methodologies in risk theory (ruin theory) as well as their mathematical validities. Asymptotic theory of parametric and nonparametric inference for the ruin-related quantities is discussed under the setting of not only classical compound Poisson risk processes (Cramér–Lundberg model) but also more general Lévy insurance risk processes. The recent development of risk theory can deal with many kinds of ruin-related quantities: the probability of ruin as well as Gerber–Shiu’s discounted penalty function, both of which are useful in insurance risk management and in financial credit risk analysis. In those areas, the common stochastic models are used in the context of the structural approach of companies’ default. So far, the probabilistic point of view has been the main concern for academic researchers. However, this book emphasizes the statistical point of view because identifying the risk model is always necessary and is crucial in the final step of practical risk management.
Author: Rob Kaas Publisher: Springer Science & Business Media ISBN: 3540867368 Category : Business & Economics Languages : en Pages : 394
Book Description
Modern Actuarial Risk Theory contains what every actuary needs to know about non-life insurance mathematics. It starts with the standard material like utility theory, individual and collective model and basic ruin theory. Other topics are risk measures and premium principles, bonus-malus systems, ordering of risks and credibility theory. It also contains some chapters about Generalized Linear Models, applied to rating and IBNR problems. As to the level of the mathematics, the book would fit in a bachelors or masters program in quantitative economics or mathematical statistics. This second and.
Author: N.U. Prabhu Publisher: Springer Science & Business Media ISBN: 1461217423 Category : Mathematics Languages : en Pages : 218
Book Description
A self-contained treatment of stochastic processes arising from models for queues, insurance risk, and dams and data communication, using their sample function properties. The approach is based on the fluctuation theory of random walks, L vy processes, and Markov-additive processes, in which Wiener-Hopf factorisation plays a central role. This second edition includes results for the virtual waiting time and queue length in single server queues, while the treatment of continuous time storage processes is thoroughly revised and simplified. With its prerequisite of a graduate-level course in probability and stochastic processes, this book can be used as a text for an advanced course on applied probability models.
Author: Peter Kotelenez Publisher: Springer Science & Business Media ISBN: 0387743170 Category : Mathematics Languages : en Pages : 452
Book Description
Stochastic Partial Differential Equations analyzes mathematical models of time-dependent physical phenomena on microscopic, macroscopic and mesoscopic levels. It provides a rigorous derivation of each level from the preceding one and examines the resulting mesoscopic equations in detail. Coverage first describes the transition from the microscopic equations to the mesoscopic equations. It then covers a general system for the positions of the large particles.
Author: Gerhard Winkler Publisher: Springer Science & Business Media ISBN: 3642557600 Category : Mathematics Languages : en Pages : 389
Book Description
"This book is concerned with a probabilistic approach for image analysis, mostly from the Bayesian point of view, and the important Markov chain Monte Carlo methods commonly used....This book will be useful, especially to researchers with a strong background in probability and an interest in image analysis. The author has presented the theory with rigor...he doesn’t neglect applications, providing numerous examples of applications to illustrate the theory." -- MATHEMATICAL REVIEWS
Author: Paul Glasserman Publisher: Springer Science & Business Media ISBN: 9780387004518 Category : Business & Economics Languages : en Pages : 624
Book Description
From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis
Author: Liang Peng Publisher: Academic Press ISBN: 012804750X Category : Mathematics Languages : en Pages : 182
Book Description
Heavy tailed data appears frequently in social science, internet traffic, insurance and finance. Statistical inference has been studied for many years, which includes recent bias-reduction estimation for tail index and high quantiles with applications in risk management, empirical likelihood based interval estimation for tail index and high quantiles, hypothesis tests for heavy tails, the choice of sample fraction in tail index and high quantile inference. These results for independent data, dependent data, linear time series and nonlinear time series are scattered in different statistics journals. Inference for Heavy-Tailed Data Analysis puts these methods into a single place with a clear picture on learning and using these techniques. - Contains comprehensive coverage of new techniques of heavy tailed data analysis - Provides examples of heavy tailed data and its uses - Brings together, in a single place, a clear picture on learning and using these techniques
Author: Nanak Chand Publisher: Trafford Publishing ISBN: 1553957741 Category : Business & Economics Languages : en Pages : 126
Book Description
Given the risk characteristics and the observed claim cost for the experience period, this book describes some ways in which statistical methods can be used in the calculation of net premiums for individual groups having non-identical risk characteristics and credibility generally less than one. The applications result in unique credibility formulas that take into account the individual characteristics, and are expected to provide adequate, equitable, and competitive premiums. The underlying methods are designed to be consistent with current actuarial practice, though giving attention to occasional need for suitable modifications. Since stop loss claim costs are a function of the behavior of the tails of their respective distributions, this part of the book assesses such claim cost using well established parametric models, and provides comprehensive tables of the corresponding stop loss premiums.
Author: Yasutaka Shimizu
Author: Yasutaka Shimizu
Author: Rob Kaas
Author: Subhashis Ghosal
Author: N.U. Prabhu
Author: Aleksandr Alekseevich Borovkov
Author: Peter Kotelenez
Author: Gerhard Winkler
Author: Paul Glasserman
Author: Liang Peng
Author: Nanak Chand