Search results for "Autore"
showing 10 items of 352 documents
Nonlinear impact estimation in spatial autoregressive models
2018
International audience; This paper extends the literature on the calculation and interpretation of impacts for spatial autoregressive models. Using a Bayesian framework, we show how the individual direct and indirect impacts associated with an exogenous variable introduced in a nonlinear way in such models can be computed, theoretically and empirically. Rather than averaging the individual impacts, we suggest to graphically analyze them along with their confidence intervals calculated from Markov chain Monte Carlo (MCMC). We also explicitly derive the form of the gap between individual impacts in the spatial autoregressive model and the corresponding model without a spatial lag and show, in…
The effects of fiscal policy shocks on the business environment
2021
Fiscal policy influences economic conditions through public spending and taxes, generating positive or negative impulses, both on short and long term. The present research focuses on analysing the effects of the discretionary changes in the fiscal policy in seven post-communist countries of the European Union during the period 2000–2018. The autoregressive distributed lag model (ARDL) has been applied in order to obtain the convergence rates to equilibrium with a clear analysis of the periods needed to achieve the long-run fiscal sustainability. Also, the error correction vector model (VECM), which is based on the autoregressive vector (VAR) model, has been used in the second part of the an…
Temperature and seasonality influences on Spanish electricity load
2002
Abstract Deregulation of the Spanish electricity market in 1998 and the possible listing of electricity or weather derivative contracts have encouraged the study of the relationship between electricity demand and weather in Spain. In this paper, a transfer function intervention model is developed for forecasting daily electricity load from cooling and heating degree–days. The influence of weather and seasonality is proved, and is significant even when the autoregressive effects and the dynamic specification of the temperature are taken into account. The estimated general model shows a high predictive power. The results and information presented in this paper could be of interest for current…
No linealidad y asimetría en el proceso generador del Índice Ibex35
2013
This paper analyzes the behavior of Ibex35 from January 1999 to December 2001, in order to check if it follows a different process from random walk so its return is not a white noise and it can be predictable, against the efficient market hypothesis. For that, a nonlinear generating process of return will be considered and a STAR-APARCH model will be specified. This model allows a nonlinear behavior in the conditional mean and in the conditional variance. The empirical results show that the Ibex35 follows a nonlinear and asymmetric process, both in the conditional mean as in the conditional variance, so the weak-version of efficient market hypothesis is rejected. El trabajo analiza el compo…
The Influence of Oil Price on Renewable Energy Stock Prices: An Analysis for Entrepreneurs
2020
Abstract This study investigates the relationship between oil price fluctuations and renewable energy stock returns using daily data on Brent crude oil prices and global renewable energy stock market indices between 29 November 2010 and 18 February 2020. The investigation is based on the existing evidence on positive correlations between stock prices and oil prices, but it also considers the shift from non-renewable to renewable sources of energy. A two-stage GARCH(1,1) model and a Granger causality test were applied. Our results show that volatility clustering is present in the renewable energy companies‘ stock prices, but, oil price volatility does not seem to induce any significant effec…
On the property of diffusion in the spatial error model.
2005
International audience; The aim of this paper is to illustrate the property of global spillover effects in the first-order spatial autoregressive error model and the associated diffusion process of spatial shocks. An application is provided on a sample of 145 regions over 1989–1999 and highlights the most influential regions.
ESCAPE TIMES IN STOCK MARKETS
2005
We study the statistical properties of escape times for stock price returns in the Wall Street market. In particular we get the escape time distribution for real data from daily transactions and for three models: (i) the Wiener process with drift and a constant market volatility, (ii) Heston and (iii) GARCH models, where the volatility is a stochastic process. We find that the first model is unable to catch all the features of the escape time distribution of real data. Moreover, the Heston model describes the probability density function for both return and escape times better than the GARCH model.
Deregulated Electric Energy Price Forecasting in NordPool Market using Regression Techniques
2019
Deregulated electricity market day-ahead electrical energy price forecasting is important. It is influenced by external parameters and it is a complicated function. In this work two neighboring regions in the NordPool market are analyzed to provide day-ahead electrical price forecasting using regression techniques. The characteristics of the NordPool market trading behavior leads to unanticipated price peaks at daily, weekly and annual level. The considered two Nordic regions have different energy generation sources (e.g Norway has controllable hydro power, Denmark has non-controllable wind-power) therefore day-ahead electrical energy price forecasting in deregulated market for these two ne…
Spectral decomposition of cerebrovascular and cardiovascular interactions in patients prone to postural syncope and healthy controls.
2022
We present a framework for the linear parametric analysis of pairwise interactions in bivariate time series in the time and frequency domains, which allows the evaluation of total, causal and instantaneous interactions and connects time- and frequency-domain measures. The framework is applied to physiological time series to investigate the cerebrovascular regulation from the variability of mean cerebral blood flow velocity (CBFV) and mean arterial pressure (MAP), and the cardiovascular regulation from the variability of heart period (HP) and systolic arterial pressure (SAP). We analyze time series acquired at rest and during the early and late phase of head-up tilt in subjects developing or…
NARX Models of an Industrial Power Plant Gas Turbine
2005
This brief reports the experience with the identification of a nonlinear autoregressive with exogenous inputs (NARX) model for the PGT10B1 power plant gas turbine manufactured by General Electric-Nuovo Pignone. Two operating conditions of the turbine are considered: isolated mode and nonisolated mode. The NARX model parameters are estimated iteratively with a Gram-Schmidt procedure, exploiting both forward and stepwise regression. Many indexes have been evaluated and compared in order to perform subset selection in the functional basis set and determine the structure of the nonlinear model. Various input signals (from narrow to broadband) for identification and validation have been consider…