11,618 research outputs found

    Copulas in finance and insurance

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    Copulas provide a potential useful modeling tool to represent the dependence structure among variables and to generate joint distributions by combining given marginal distributions. Simulations play a relevant role in finance and insurance. They are used to replicate efficient frontiers or extremal values, to price options, to estimate joint risks, and so on. Using copulas, it is easy to construct and simulate from multivariate distributions based on almost any choice of marginals and any type of dependence structure. In this paper we outline recent contributions of statistical modeling using copulas in finance and insurance. We review issues related to the notion of copulas, copula families, copula-based dynamic and static dependence structure, copulas and latent factor models and simulation of copulas. Finally, we outline hot topics in copulas with a special focus on model selection and goodness-of-fit testing

    Multistability of a Josephson parametric amplifier coupled to a mechanical resonator

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    We study the dynamics of Josephson Parametric Amplifier (JPA) coupled to a mechanical oscillator, as realised with a dc Superconducting Quantum Interference Device (SQUID) with an embedded movable arm. We analyse this system in the regime when the frequency of the mechanical oscillator is comparable in magnitude with the plasma oscillation of the SQUID. When the nano-mechanical resonator is driven, it strongly affects the dynamics of the JPA. We show that this coupling can considerably modify the dynamics of JPA and induce its multistability rather than common bistability. This analysis is relevant if one considers a JPA for detection of mechanical motion.Comment: 8 pages, 5 figures, accepted for publication in Phys. Rev.

    Copulas in finance and insurance

    Get PDF
    Copulas provide a potential useful modeling tool to represent the dependence structure among variables and to generate joint distributions by combining given marginal distributions. Simulations play a relevant role in finance and insurance. They are used to replicate efficient frontiers or extremal values, to price options, to estimate joint risks, and so on. Using copulas, it is easy to construct and simulate from multivariate distributions based on almost any choice of marginals and any type of dependence structure. In this paper we outline recent contributions of statistical modeling using copulas in finance and insurance. We review issues related to the notion of copulas, copula families, copula-based dynamic and static dependence structure, copulas and latent factor models and simulation of copulas. Finally, we outline hot topics in copulas with a special focus on model selection and goodness-of-fit testing.Dependence structure, Extremal values, Copula modeling, Copula review

    An Econometric Model for Forecasting Internal Taxes: A National Level Approach

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    Tax revenue forecasting is an essential input in the budgetary process. The ability to project and forecast future tax collections is an important element in the identification of future budgetary gaps and in the planning of new tax measures that may be needed to meet these needs. In addition, taxes play a major role in financing of the country’s economic and social development. It is the purpose of this paper to develop, specify and estimate a forecasting model for internal taxes. In particular, this paper attempts to estimate a tax-forecasting model that has a higher level of disaggregation.econometric modeling, taxation

    Optimal railway infrastructure maintenance and repair policies to manage risk under uncertainty with adaptive control

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    The aim of this paper is to apply two adaptive control formulations under uncertainty, say open-loop and closed-loop, to the process of developing maintenance and repair policies for railway infrastructures. To establish the optimal maintenance and repair policies for railway lines, we use a previous design of risk model based on two factors: the criticality and the deterioration ratios of the facilities. Thus, our theory benefits from the Reliability Centered Management methodology application, but it also explicitly models uncertainty in characterizing a facility deterioration rate to decide the optimal policy to maintain the railway infrastructures. This may be the major contribution of this work. To verify the models presented, a computation study has been developed and tested for a real scenario: the railway line Villalba-Cercedilla in Madrid (Spain). Our results demonstrate again that applying any adaptive formulation, the cost of the railway lines maintenance shown is decreased. Moreover applying a Closed Loop Formulation the cost associated to the risk takes smaller values (40% less cost for the same risk than the deterministic approach), but with an Open Loop formulation the generated risk in the railway line is also smaller

    Quantum relative positioning in Hilbert space

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    A new class of state transformations that are quantum mechanically prohibited is introduced. These can be seen as the generalization of the universal-NOT transformation which, for all pure inputs state of a given Hilbert space produces pure outputs whose projection on the original state is fixed to a value smaller than one. The case of not pure output states is also addressed. We give an application of these transformations in the context of separability criteria.Comment: 5 pages, 1 figure; new material added: in particular we present an application of quantum movers in the context of separability criteria. Typos corrected. Phys. Rev. A, accepted for publicatio
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