Search results for "Autore"

Outlier detection with automatic modelling: TRAMO/SEATS versus X-12-ARIMA

2012

Tests for real and complex unit roots in vector autoregressive models

2014

The article proposes new tests for the number of real and complex unit roots in vector autoregressive models. The tests are based on the eigenvalues of the sample companion matrix. The limiting distributions of the eigenvalues converging to the unit eigenvalues turn out to be of a non-standard form and expressible in terms of Brownian motions. The tests are defined such that the null distributions related to eigenvalues +/-1 are the same. The tests for the unit eigenvalues with nonzero imaginary part are defined independently of the angular frequency. When the tests are adjusted for deterministic terms, the null distributions usually change. Critical values are tabulated via simulations. Al…

Dynamic copula models for the spark spread

2011

We propose a non-symmetric copula to model the evolution of electricity and gas prices by a bivariate non-Gaussian autoregressive process. We identify the marginal dynamics as driven by normal inverse Gaussian processes, estimating them from a series of observed UK electricity and gas spot data. We estimate the copula by modeling the difference between the empirical copula and the independent copula. We then simulate the joint process and price options written on the spark spread. We find that option prices are significantly influenced by the copula and the marginal distributions, along with the seasonality of the underlying prices.

Digital generation of multivariate wind field processes

2001

Abstract A very efficient procedure for the generation of multivariate wind velocity stochastic processes by wave superposition as well as autoregressive time series is proposed in this paper. The procedure starts by decomposing the wind velocity field into a summation of fully coherent independent vector processes using the frequency dependent eigenvectors of the Power Spectral Density matrix. It is shown that the application of the method allows to show some very interesting physical properties that allow to reduce drastically the computational effort. Moreover, using a standard finite element procedure for approximating the frequency dependent eigenvectors, the generation procedure requi…

Stochastic analysis of motorcycle dynamics

2011

Off-road and racing motorcycles require a particular setup of the suspensions to improve the comfort and the safety of the rider, maintaining a continuous contact between the road and the motorcycle (by means of the tires). Further, because of the ground roughness, in the case of offroad motorcycle, suspensions usually experience extreme and erratic excursions (suspension stroke) in performing their function. In this regard, the adoption of nonlinear devices can, perhaps, limit both the acceleration experienced by the sprung mass and the excursions of the suspensions. This leads to the consideration of asymmetric nonlinearly-behaving suspensions. This option, however, induces the difficulty…

Firm Size and Volatility Analysis in the Spanish Stock Market

2011

In this article, three strongly related questions are studied. First, volatility spillovers between large and small firms in the Spanish stock market are analyzed by using a conditional CAPM with an asymmetric multivariate GARCH-M covariance structure. Results show that there exist bidirectional volatility spillovers between both types of firms, especially after bad news. Second, the volatility feedback hypothesis explaining the volatility asymmetry feature is investigated. Results show significant evidence for this hypothesis. Finally, the study uncovers that conditional beta coefficient estimates within the used model are insensitive to sign and size asymmetries in the unexpected shock re…

The impact of economic and policy uncertainty shocks in Spain

2020

The purpose of this research is to quantify the impact of economic uncertainty shocks in Spain by using a structural vector autoregression (SVAR) approach with data from the first quarter of 2001 u...

Update on mechanism and therapeutic implications of spinal cord stimulation and cerebral hemodynamics: A narrative review

2017

Spinal cord stimulation (SCS) is well known for its early role in the management of chronic pain, mainly failed back surgery syndrome (FBSS), spasticity, and bowel and bladder dysfunction. In more recent years, SCS has been proposed for patients suffering from refractory angina or peripheral vasculopathies in order to gain symptom relief, thus indicating some hemodynamic effect on the peripheral circulation. Taking into account this scientific observation, since the late1980s, researchers have started to investigate the potential effect of SCS on cerebral blood flow (CBF) regulation and its possible application in certain pathological settings dealing with vascular pattern dysfunction, such…

Use of middle cerebral velocity and blood pressure for the analysis of cerebral autoregulation at various frequencies: The coherence index

1998

A common component in many protocols for the evaluation of cerebral autoregulation is the comparison of transcranial Doppler ultrasound (TCD) velocities with blood pressure recordings, in which correlations between these two signals correspond to impaired autoregulation. With long data sets and complicated paradigms, however, visual inspection alone cannot adequately distinguish random coincidence from consistent correlation in a statistically valid fashion. We suggest and illustrate the use of the coherence index for this purpose. To illustrate this technique, long-term recordings of TCD velocity and blood pressure were obtained from 6 normal subjects and using 23 data segments from 8 pati…

An identifiable model to assess frequency-domain Granger causality in the presence of significant instantaneous interactions

2010

We present a new approach for the investigation of Granger causality in the frequency domain by means of the partial directed coherence (PDC). The approach is based on the utilization of an extended multivariate autoregressive (MVAR) model, including instantaneous effects in addition to the lagged effects traditionally studied, to fit the observed multiple time series prior to PDC computation. Model identification is performed combining standard MVAR coefficient estimation with a recent technique for instantaneous causal modeling based on independent component analysis. The approach is first validated on simulated MVAR processes showing that, in the presence of instantaneous effects, only t…