Corpus ID: 27996627

Modelling Copulas : An Overview

@inproceedings{Dorey2005ModellingC,
  title={Modelling Copulas : An Overview},
  author={Martyn Dorey and Philippe Joubert},
  year={2005}
}
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13 Citations
Highly Influential Citations
2
Background Citations
6
Methods Citations
5

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13 Citations

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TLDR
A GARCH-Vine copula model to analyze the tail dependence of different stock markets based on the fat-tail and volatility clustering characteristics of financial data is proposed and the research results show that the proposed model is feasible and effective. Expand
Copula-based models in railroad maintenance and safety analysis
TLDR
The American railroad industry has been a primary stakeholder in the economic development of the nation for close to two centuries and derailments remain a major concern for the railroads due to their high consequences which include loss of life and property, disruption of services, injury, and destruction to the natural environment. Expand
Modeling tamping recovery of track geometry using the copula-based approach
TLDR
This research employs the copula models in combining arbitrary marginal distributions to form a joint multivariate distribution with the underlying dependence between the variables, which may exhibit nonlinear dependences such as tail or asymmetric dependence. Expand
Simulation-based capital models: testing, justifying and communicating choices. A report from the life aggregation and simulation techniques working party
TLDR
The practical challenges in parameterising a copula including how allowance may be made for tail dependence are described and how insurers could test, communicate and justify the choices made through the use of some examples are outlined. Expand
Time-dependent reliability analysis for deteriorating structures using imprecise probability theory
Faculty of Engineering and Information Technologies School of Civil Engineering Doctor of Philosophy
A Framework For Microgrid Planning Using Multidisciplinary Design Optimization
Construction of multivariate copulas in $n$-boxes
TLDR
The gluing method of Siburg and Stoimenov and its generalization in Mesiar et al. Expand
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References

SHOWING 1-10 OF 26 REFERENCES
A Comparative Analysis of Cdo Pricing Models Introduction
We compare some popular CDO pricing models, related to the bottom‐up approach. Dependence between default times is modelled through Gaussian, stochastic correlation, Student t, double t, Clayton and… Expand
Correlation at First Sight
The synthetic collateralized debt obligation (CDO) market has, over the last year, seen a significant increase in liquidity and transparency. The availability of published prices such as TracX and… Expand
Simulating Correlated Multivariate Pseudorandom Numbers
A modification of the Kaiser and Dichman (1962) procedure of generating multivariate random numbers with specified intercorrelation is proposed. The procedure works with positive and non-positive… Expand
Quantifying Correlated Reinsurance Exposures with Copulas
Copulas provide a convenient way to represent joint distributions. In fact the joint distribution function can be expressed as the copula function applied to the separate individual distributions.… Expand
Statistical Thought: A Perspective and History
PERSPECTIVE Preface 1. Philosophical Background 2. Statistical Induction - When and How? 3. Interpretation of Probability - Various Nuances 4. Bearing of Interpretations of Probability on Statistical… Expand
An Introduction to Copulas
TLDR
This book is aimed at graduate students in statistics or mathematics, and practicing statisticians, and requires proficiency in advanced calculus, and can serve as a very good reference on the exciting topic of wavelets. Expand
Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach
We propose a method for estimating Value at Risk VaR and related risk measures describing the tail of the conditional distribution of a heteroscedastic financial return series. Our approach combines… Expand
The Most General Methodology to Create a Valid Correlation Matrix for Risk Management and Option Pricing Purposes
We have presented two simple methods to produce a feasible (i.e. real, symmetric, and positivesemidefinite) correlation matrix when the econometric one is either noisy, unavailable, or inappropriate.… Expand
AGGREGATION OF CORRELATED RISK PORTFOLIOS: MODELS AND ALGORITHMS
This paper presents a set of tools for modeling and combining correlated risks. Various correlation structures are generated using copula, common mixture, component, and distortion models. These… Expand
Correlations and Copulas for Decision and Risk Analysis
The construction of a probabilistic model is a key step in most decision and risk analyses. Typically this is done by defining a joint distribution in terms of marginal and conditional distributions… Expand
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