5,493 research outputs found

    Estimation of Risk-Neutral Density Surfaces

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    Option price data is often used to infer risk-neutral densities for future prices of an underlying asset. Given the prices of a set of options on the same underlying asset with different strikes and maturities, we propose a nonparametric approach for estimating risk-neutral densities associated with several maturities. Our method uses bicubic splines in order to achieve the desired smoothness for the estimation and an optimization model to choose the spline functions that best fit the price data. Semidefinite programming is employed to guarantee the nonnegativity of the densities. We illustrate the process using synthetic option price data generated using log-normal and absolute diffusion processes as well as actual price data for options on the S&P500 index. We also used the risk-neutral densities that we computed to price exotic options and observed that this approach generates prices that closely approximate the market prices of these options.

    A Multi-Membership Catalogue for 1876 Open Clusters using UCAC4 data

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    The main objective of this work is to determine the cluster members of 1876 open clusters, using positions and proper motions of the astrometric catalogue UCAC4. For this purpose we apply three different methods, all them based on a Bayesian approach, but with different formulations: a purely parametric method, another completely non-parametric algorithm, and a third, recently developed by Sampedro & Alfaro, using both formulations at different steps of the whole process. The first and second statistical moments of the members phase-space subspace, obtained after applying the three methods, are compared for every cluster. Although, on average, the three methods yield similar results, specific differences between them, as well as for some particular clusters, are also present. The comparison with other published catalogues shows good agreement. We have also estimated for the first time the mean proper motion for a sample of 18 clusters. The results are organized in a single catalogue formed by two main files, one with the most relevant information for each cluster, partially including that in UCAC4, and the other showing the individual membership probabilities for each star in the cluster area. The final catalogue, with an interface design that enables an easy interaction with the user, is available in electronic format at SSG-IAA (http://ssg.iaa.es/en/content/sampedro-cluster-catalog) website.Comment: Accepted for publication in MNRAS. 9 pages, 3 figures, 6 table

    Some boundary effects in quantum field theory

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    We have constructed a quantum field theory in a finite box, with periodic boundary conditions, using the hypothesis that particles living in a finite box are created and/or annihilated by the creation and/or annihilation operators, respectively, of a quantum harmonic oscillator on a circle. An expression for the effective coupling constant is obtained showing explicitly its dependence on the dimension of the box.Comment: 12 pages, Late

    Generalized Rate-Code Model for Neuron Ensembles with Finite Populations

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    We have proposed a generalized Langevin-type rate-code model subjected to multiplicative noise, in order to study stationary and dynamical properties of an ensemble containing {\it finite} NN neurons. Calculations using the Fokker-Planck equation (FPE) have shown that owing to the multiplicative noise, our rate model yields various kinds of stationary non-Gaussian distributions such as gamma, inverse-Gaussian-like and log-normal-like distributions, which have been experimentally observed. Dynamical properties of the rate model have been studied with the use of the augmented moment method (AMM), which was previously proposed by the author with a macroscopic point of view for finite-unit stochastic systems. In the AMM, original NN-dimensional stochastic differential equations (DEs) are transformed into three-dimensional deterministic DEs for means and fluctuations of local and global variables. Dynamical responses of the neuron ensemble to pulse and sinusoidal inputs calculated by the AMM are in good agreement with those obtained by direct simulation. The synchronization in the neuronal ensemble is discussed. Variabilities of the firing rate and of the interspike interval (ISI) are shown to increase with increasing the magnitude of multiplicative noise, which may be a conceivable origin of the observed large variability in cortical neurons.Comment: 19 pages, 9 figures, accepted in Phys. Rev. E after minor modification

    Molecules in external fields: a semiclassical analysis

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    We undertake a semiclassical analysis of the spectral properties (modulations of photoabsorption spectra, energy level statistics) of a simple Rydberg molecule in static fields within the framework of Closed-Orbit/Periodic-Orbit theories. We conclude that in addition to the usual classically allowed orbits one must consider classically forbidden diffractive paths. Further, the molecule brings in a new type of 'inelastic' diffractive trajectory, different from the usual 'elastic' diffractive orbits encountered in previous studies of atomic and analogous systems such as billiards with point-scatterers. The relative importance of inelastic versus elastic diffraction is quantified by merging the usual Closed Orbit theory framework with molecular quantum defect theory.Comment: 4 pages, 3 figure

    Molecular Line Profile Fitting with Analytic Radiative Transfer Models

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    We present a study of analytic models of starless cores whose line profiles have ``infall asymmetry,'' or blue-skewed shapes indicative of contracting motions. We compare the ability of two types of analytical radiative transfer models to reproduce the line profiles and infall speeds of centrally condensed starless cores whose infall speeds are spatially constant and range between 0 and 0.2 km s-1. The model line profiles of HCO+ (J=1-0) and HCO+ (J=3-2) are produced by a self-consistent Monte Carlo radiative transfer code. The analytic models assume that the excitation temperature in the front of the cloud is either constant (``two-layer'' model) or increases inward as a linear function of optical depth (``hill'' model). Each analytic model is matched to the line profile by rapid least-squares fitting. The blue-asymmetric line profiles with two peaks, or with a blue shifted peak and a red shifted shoulder, can be well fit by the ``HILL5'' model (a five parameter version of the hill model), with an RMS error of 0.02 km s-1. A peak signal to noise ratio of at least 30 in the molecular line observations is required for performing these analytic radiative transfer fits to the line profiles.Comment: 48 pages, 20 figures, accepted for publication in Ap
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