Showing 1 - 10 of 21
This paper is concerned with modelling time series by single hidden layer feedforward neural network models. A coherent modelling strategy based on statistical inference is presented. Variable selection is carried out using existing techniques. The problem of selecting the number of hidden units...
Persistent link: https://www.econbiz.de/10011807289
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse,high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly,...
Persistent link: https://www.econbiz.de/10011807426
This paper analyses the main statistical properties of the Emerging Market Bond Index (EMBI), namely long-range dependence or persistence, non-linearities, and structural breaks, in four Latin American countries (Argentina, Brazil, Mexico, Venezuela). For this purpose it uses a fractional...
Persistent link: https://www.econbiz.de/10011392136
This paper analyses the main statistical properties of the Emerging Market Bond Index (EMBI), namely long-range dependence or persistence, non-linearities, and structural breaks, in four Latin American countries (Argentina, Brazil, Mexico, Venezuela). For this purpose it uses a fractional...
Persistent link: https://www.econbiz.de/10011392612
We consider a new method to estimate causal effects when a treated unit suffers a shock or an intervention, such as a policy change, but there is not a readily available control group or counterfactual. We propose a two-step approach where in the first stage an artificial counterfactual is...
Persistent link: https://www.econbiz.de/10011523575
In this paper we show the validity of the adaptive LASSO procedure in estimating stationary ARDL(p,q) models with GARCH innovations. We show that, given a set of initial weights, the adaptive Lasso selects the relevant variables with probability converging to one. Afterwards, we show that the...
Persistent link: https://www.econbiz.de/10010505034
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume that both the number of covariates in the model and the number of candidate variables can increase with the sample size (polynomially or geometrically). In other...
Persistent link: https://www.econbiz.de/10010505038
In this paper we examine the forecast accuracy of linear autoregressive, smooth transition autoregressive (STAR), and neural network (NN) time series models for 47 monthly macroeconomic variables of the G7 economies. Unlike previous studies that typically consider multiple but fixed model...
Persistent link: https://www.econbiz.de/10002127012
Over recent years, several nonlinear time series models have been proposed in the literature. One model that has found a large number of successful applications is the threshold autoregressive model (TAR). The TAR model is a piecewise linear process whose central idea is to change the parameters...
Persistent link: https://www.econbiz.de/10001599987
A wide variety of conditional and stochastic variance models has been used to estimate latent volatility (or risk). In both the conditional and stochastic volatility literature, there has been some confusion between the definitions of asymmetry and leverage. In this paper, we first show the...
Persistent link: https://www.econbiz.de/10013156686