We consider the problem of estimating the conditional quantile of a time series fYtg at time t given covariates Xt, where Xt can ei- ther exogenous variables or lagged variables of Yt . The conditional quantile is estimated by inverting a kernel estimate of the conditional distribution function,...

Recently, with the development of financial markets and due to the importance of these markets and their close relationship with other macroeconomic variables, using advanced mathematical models with complicated structures for forecasting these markets has become very popular. Besides, neural...

This entry for the New Palgrave covers developments in nonlinear time series analysis over the last 25 years.

There is an increasing awareness of the potential of nonlinear modeling in regional science, which can partly be explained by the recognition of the limitations of conventional equilibrium models in complex situationsand partly by the easy availability and accessibility of sophisticated...

The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model) and a regressive (Auto Regressive Fractionally Integrated Moving Average model which...

Existen diversas metodologías para calcular el valor en riesgo (VaR) que pretenden capturar principalmente el riesgo de mercado al que están expuestas las instituciones financieras. Siendo el modelo de valor en riesgo condicional autorregresivo (CAViaR) de Engle y Manganelli (1999, 2001, 2004)...

Esta investigación tiene como propósito implementar la metodología de regresión cuantil bayesiana en el cálculo del valor en riesgo (VaR, en inglés) en el mercado de valores colombiano. Para este objetivo se valoran algunos requerimientos regulatorios sobre riesgo de mercado definidos por...

The purpose of this paper is to present a new kind of discrete choice model called "Generalized Neural Logit Model" applied exemplarily to the case of airport and access mode choice. This approach employs neural networks to model the utility function of a discrete choice model and correlations...

Cet article fournit quelques resultats de previsions de pics de pollution d'ozone pour la station de mesure de Vitrolles, situee dans l'Aire Metropolitaine Marseillaise. Nous presentons d'abord la methode de regression par arbre et une idee de stabilisation par Agregatopm par Bootstrap. Ces...

Apres une presentation de la construction de predicteurs par arbre de classification, nous nous interessons a l'instabilite de cette methode et proposons une methodologie dans laquelle intervient le bootstrap. Une etude empirique detaillee illustre ce travail.