Portmanteau goodness-of-fit test for asymmetric power GARCH models

The asymptotic distribution of a vector of autocorrelations of squared residuals is derived for a wide class of asymmetric GARCH models. Portmanteau adequacy tests are deduced. %gathered These results are obtained under moment assumptions on the iid process, but fat tails are allowed for the observed process, which is particularly relevant for series of financial returns. A Monte Carlo experiment and an illustration to financial series are also presented.ARCH models; Leverage effect; Portmanteau test; Goodness-of-fit test; Diagnostic checking

Computing and estimating information matrices of weak arma models

Numerous time series admit "weak" autoregressive-moving average (ARMA) representations, in which the errors are uncorrelated but not necessarily independent nor martingale differences. The statistical inference of this general class of models requires the estimation of generalized Fisher information matrices. We give analytic expressions and propose consistent estimators of these matrices, at any point of the parameter space. Our results are illustrated by means of Monte Carlo experiments and by analyzing the dynamics of daily returns and squared daily returns of financial series.Asymptotic relative efficiency (ARE); Bahadur's slope; Information matrices; Lagrange Multiplier test; Nonlinear processes; Wald test; Weak ARMA models

Estimación no paramétrica de la densidad y de la regresión - previsión no paramétrica

We begin with a short wiew of non parametric estimation of density and regression; then we give details and interpretation of a forecasting method, called non parametric forecasting . We show different aspects, technical as well as practical, and we compare the method with the Box and Jenkings methodology, over some examples.Keywords: Non – parametric statistics, time series, forecasting, regression, Kernels.Después de un vistazo sobre la estimación no paramétrica de la densidad y de la regresión, detallamos e interpretamos un método de previsión, llamado de previsión no paramétrica. Mostramos los diferentes aspectos tanto técnicos como prácticos, y comparamos el método propuesto sobre algunos ejemplos respecto a la metodología de Box y Jenkins.Palabras clave: Estadística no paramétrica, series de tiempo, previsión, regresión, núcleos

Portmanteau goodness-of-fit test for asymmetric power GARCH models

The asymptotic distribution of a vector of autocorrelations of squared residuals is derived for a wide class of asymmetric GARCH models. Portmanteau adequacy tests are deduced. %gathered These results are obtained under moment assumptions on the iid process, but fat tails are allowed for the observed process, which is particularly relevant for series of financial returns. A Monte Carlo experiment and an illustration to financial series are also presented

Computing and estimating information matrices of weak arma models

Numerous time series admit "weak" autoregressive-moving average (ARMA) representations, in which the errors are uncorrelated but not necessarily independent nor martingale differences. The statistical inference of this general class of models requires the estimation of generalized Fisher information matrices. We give analytic expressions and propose consistent estimators of these matrices, at any point of the parameter space. Our results are illustrated by means of Monte Carlo experiments and by analyzing the dynamics of daily returns and squared daily returns of financial series

Chemodynamics of a simulated disc galaxy: initial mass functions and Type Ia supernova progenitors

We trace the formation and advection of several elements within a cosmological adaptive mesh refinement simulation of an L� galaxy. We use nine realizations of the same initial conditions with different stellar initial mass functions (IMFs), mass limits for Type II and Type Ia supernovae (SNII, SNIa) and stellar lifetimes to constrain these subgrid phenomena. Our code includes self-gravity, hydrodynamics, star formation, radiative cooling and feedback from multiple sources within a cosmological framework. Under our assumptions of nucleosynthesis we find that SNII with progenitor masses of up to 100 M� are required to match low-metallicity gas oxygen abundances. Tardy SNIa are necessary to reproduce the classical chemical evolution ‘knee’ in [O/Fe]–[Fe/H]: more prompt SNIa delayed time distributions do not reproduce this feature. Within our framework of hydrodynamical mixing of metals and galaxy mergers we find that chemical evolution is sensitive to the shape of the IMF and that there exists a degeneracy with the mass range of SNII. We look at the abundance plane and present the properties of different regions of the plot, noting the distinct chemical properties of satellites and a series of nested discs that have greater velocity dispersions are more α-rich and metal poor with age

Properties of the Binary Black Hole Merger GW150914

On September 14, 2015, the Laser Interferometer Gravitational-Wave Observatory (LIGO) detected a gravitational-wave transient (GW150914); we characterize the properties of the source and its parameters. The data around the time of the event were analyzed coherently across the LIGO network using a suite of accurate waveform models that describe gravitational waves from a compact binary system in general relativity. GW150914 was produced by a nearly equal mass binary black hole of masses 36+5−4M⊙ and 29+4−4M⊙; for each parameter we report the median value and the range of the 90% credible interval. The dimensionless spin magnitude of the more massive black hole is bound to be <0.7 (at 90% probability). The luminosity distance to the source is 410+160−180  Mpc, corresponding to a redshift 0.09+0.03−0.04 assuming standard cosmology. The source location is constrained to an annulus section of 610  deg2, primarily in the southern hemisphere. The binary merges into a black hole of mass 62+4−4M⊙ and spin 0.67+0.05−0.07. This black hole is significantly more massive than any other inferred from electromagnetic observations in the stellar-mass regime

Sur l'estimation asymptotique d'une classe de paramètres fonctionnels.

International audienceIn This work, the asymptotic estimation of a class F of functional parameters is studied. This class includes the classical parameters under some hypothesis of regularity. This class is especially characterized by the fact that the class F*s elements can be written like sequences'limits of the expected value of a sample random variables function.Some results about the uniform a.s. convergence of "natural" estimators of class F's elements, and also a speed of convergence are given, explained by examples.Cet article est essentiellement consacré à l'estimation asymptotique d'une classe F de paramètres fonctionnels, classe qui contient, sous certaines hypothèses de régularité, les paramètres classiques. Cette classe F est surtout caractérisée par le fait que les éléments de F peuvent s'écrira comme des limites de suites d'espérances mathématiques des variables de l'échantillon.Des résultats relatifs à la convergence uniforme p.s. des estimateurs "naturels" des éléments de F, ainsi qu'une vitesse de convergence sont fournis, le tout illustrés d'exemples

Processus Self-similaires

International audienceDans cet article, nous passons en revue les propriétés générales des processus self-similaires, en insistant sur les processus self-similaires à accroissements stationnaires. Nous indiquons aussi quelques propriétés des lois marginales, et des trajectoires. Un dernier paragraphe est également consacré à l’estimation du coefficient de self-similarité