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Modelling financial time series using reflections of copulas

Jozef Komorník, Magda Komorníková (2013)

Kybernetika

We have intensified studies of reflections of copulas (that we introduced recently in [6]) and found that their convex combinations exhibit potentially useful fitting properties for original copulas of the Normal, Frank, Clayton and Gumbel types. We show that these properties enable us to construct interesting models for the relations between investment in stocks and gold.

Models for stochastic mortality

Jan Iwanik (2007)

Applicationes Mathematicae

This paper is an attempt to present and analyse stochastic mortality models. We propose a couple of continuous-time stochastic models that are natural generalizations of the Gompertz law in the sense that they reduce to the Gompertz function when the volatility parameter is zero. We provide a statistical analysis of the available demographic data to show that the models fit historical data well. Finally, we give some practical examples for the multidimensional models.

More general credibility models

Virginia Atanasiu (2009)

Mathematica Bohemica

This communication gives some extensions of the original Bühlmann model. The paper is devoted to semi-linear credibility, where one examines functions of the random variables representing claim amounts, rather than the claim amounts themselves. The main purpose of semi-linear credibility theory is the estimation of μ 0 ( θ ) = E [ f 0 ( X t + 1 ) | θ ] (the net premium for a contract with risk parameter θ ) by a linear combination of given functions of the observable variables: X ̲ ' = ( X 1 , X 2 , ... , X t ) . So the estimators mainly considered here are linear...

Multistage multivariate nested distance: An empirical analysis

Sebastiano Vitali (2018)

Kybernetika

Multistage stochastic optimization requires the definition and the generation of a discrete stochastic tree that represents the evolution of the uncertain parameters in time and space. The dimension of the tree is the result of a trade-off between the adaptability to the original probability distribution and the computational tractability. Moreover, the discrete approximation of a continuous random variable is not unique. The concept of the best discrete approximation has been widely explored and...

Multivariate extensions of expectiles risk measures

Véronique Maume-Deschamps, Didier Rullière, Khalil Said (2017)

Dependence Modeling

This paper is devoted to the introduction and study of a new family of multivariate elicitable risk measures. We call the obtained vector-valued measures multivariate expectiles. We present the different approaches used to construct our measures. We discuss the coherence properties of these multivariate expectiles. Furthermore, we propose a stochastic approximation tool of these risk measures.

Multivariate smooth transition AR model with aggregation operators and application to exchange rates

Tomáš Bacigál (2007)

Kybernetika

An overview of multivariate modelling based on logistic and exponential smooth transition models with transition variable generated by aggregation operators and orders of auto and exogenous regression selected by information criterion separately for each regime is given. Model specification procedure is demonstrated on trivariate exchange rates time series. The application results show satisfactory improvement in fit when particular aggregation operators are used. Source code in the form of Mathematica...

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