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Principles of Copula Theory

Principles of Copula Theory explores the state of the art on copulas and provides you with the foundation to use copulas in a variety;

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Simulating Copulas

'The book remains a valuable tool both for statisticians who are already familiar with the theory of copulas and just need to develop;

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Financial Engineering with Copulas Explained

This is a succinct guide to the application and modelling of dependence models or copulas in the financial markets. First applied to credit;

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Copulas

apply them to your own. Copulas involves a detailed analysis of the field of financial risk management and derivative pricing, and: introduces;

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Copulas for Risk Management

of copulas in many fields. The copula-based approach is implemented by specifying the margins and the dependence structure represented by a certain;

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Copula Modeling

copulas is that estimation and inference are based on standard maximum likelihood procedures. Thus, copulas can be estimated using desktop;

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Dynamic Copulas for Finance

in the dependence structure. Alternatively, Copulas are a more flexible dependence measurement. This book focuses on the development of Dynamic;

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Dependence Modeling with Copulas

Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including;

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Dependence Modeling with Copulas

Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including;

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Simulating Copulas

This book provides the reader with a background on simulating copulas and multivariate distributions in general. It unifies the scattered;

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Copulas and Its Application in Hydrology and Water Resources

practical applications for multivariate hydrological analysis using copulas. In addition, it extends the traditional bivariate model to trivariate;

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Elements of Copula Modeling with R

This book introduces the main theoretical findings related to copulas and shows how statistical modeling of multivariate continuous;

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Copulas and their Applications in Water Resources Engineering

in many cases. Recent years have therefore witnessed numerous applications of copulas to multivariate hydrologic frequency analyses. This book;

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Copula Theory and Its Applications

Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility;

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Missing Data Methods

Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators;

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Missing Data Methods

Analysis of Multivariate Sample Selection Models Using Gaussian Copulas; Consistent Estimation and Orthogonality; and Likelihood-Based Estimators;

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The Valuation of Multivariate Options

through copulas has become common. Copulas are multivariate distributions on the d-dimensional unit-hyper-square which couples d marginal;

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Performance- und Risikomessung bei Hedgefonds

, wie getestet wird, ob eine Normalverteilung der Renditen vorliegt. Ein weiteres Kapitel besch ftigt sich mit dem Themengebiet der Copulas. Copulas k;

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Statistical Analysis of Financial Data in S-plus

introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal;

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Copula Methods in Finance

explains copulas by means of applications to major topics in derivative pricing and credit risk analysis. Examples include pricing of the main;

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Introduction to Bayesian Estimation and Copula Models of Dependence

, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management;

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Aggregation Functions in Theory and in Practice

of these functions include means, t-norms and t-conorms, copulas and fuzzy integrals (e.g., the Choquet and Sugeno integrals).;

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Correlated Data Analysis

models, this book covers new topics on joint regression analysis based on Gaussian copulas.;

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Coping with Risk in Agriculture

the analysis of production and the use of copulas to better model stochastic dependency. Aiming to introduce agricultural decision making;

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Coping with Risk in Agriculture

the analysis of production and the use of copulas to better model stochastic dependency. Aiming to introduce agricultural decision making;

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R In Finance And Economics

statistical methods like linear regression, econometrics (GARCH etc), Copulas, etc. Moreover, the book demonstrates latest research methods with;

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Einde inhoud

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