Results 21 to 30 of about 44,033 (313)
Revisiting the Copula-Based Trading Method Using the Laplace Marginal Distribution Function
Pairs trading under the copula approach is revisited in this paper. It is well known that financial returns arising from indices in markets may not follow the features of normal distribution and may exhibit asymmetry or fatter tails, in particular.
Tayyebeh Nadaf +2 more
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Copula cosmology: Constructing a likelihood function [PDF]
To estimate cosmological parameters from a given dataset, we need to construct a likelihood function, which sometimes has a complicated functional form. We introduce the copula, a mathematical tool to construct an arbitrary multivariate distribution function from one-dimensional marginal distribution functions with any given dependence structure. It is
Sato, Masanori +2 more
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Modelling stochastic bivariate mortality [PDF]
Stochastic mortality, i.e. modelling death arrival via a jump process with stochastic intensity, is gaining increasing reputation as a way to represent mortality risk.
A J G Cairns +36 more
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Performance of Archimedean copula functions in annual flood estimation, Case study: Qarah-Soo Watershed [PDF]
Flood is known as one of the most devastating natural hazards which cause great damages to human societies, municipal, industrial and agricultural centers. Flood estimation in confluence points of rivers– for being the location for many infrastructures –
Sanaz Zeraati, Mohammad Zounemat-Kermani
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Information Measures via Copula Functions [PDF]
In applications of differential geometry to problems of parametric inference, the notion of divergence is often used to measure the separation between two parametric densities. Among them, in this paper, we will verify measures such as Kullback-Leibler information, J-divergence, Hellinger distance, α-Divergence, . . . and so on.
R. Mohtashami Borzadaran, M. Amini
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TIME SERIES ANALYSIS USING COPULA GAUSS AND AR(1)-N.GARCH(1,1)
In this case, the Gaussian Copula is used to connect the data that correlates with the time and with other data sets. Most often, practitioners rely only on the linear correlation to describe the degree of dependence between two or more variables; an ...
Rezzy Eko Caraka +3 more
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Method to Select Copula Functions
Copula functions have been extensively used in applied statistics, becoming a good alternative for modeling the dependence of multivariate data. Each copula function has a different dependence structure. An important issue in these applications is the choice of an appropriate copula function model for each one; thus common classical or Bayesian ...
Jorge Alberto Achcar +2 more
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Bivariate Flood Frequency Analysis Using the Copula Archimedean Function (Gumbel–Hougaard) [PDF]
Flood is a multivariate and complex phenomenon that has a random nature. In conventional methods of flood frequency analysis, only flood peak variable is important and it is assumed that the variable under consideration follows a particular parametric ...
Mohammad Reza Goodarzi +3 more
doaj +1 more source
Modeling Insurance Claim Distribution via Mixture Distribution and Copula [PDF]
This paper analyses whether joint probability distribution function of losses due to different exposures covered under the same policy could be modeled in an appropriate manner via mixture distribution proposed and copula concept.
Saeed Bajalan +2 more
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Calibrating and Simulating Copula Functions in Financial Applications
Copula functions can be utilized in financial applications to determine the dependence structure of the financial asset returns in the portfolio. Empirical evidence has proved the inadequacy of the multi-normal distribution, traditionally adopted to ...
Annalisa Di Clemente, Claudio Romano
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