This article gives the asymptotic properties of multivariate k-nearest neighbor regression estimators for dependent variables belonging to Rd, d 1. The results derived here permit to provide consistent forecasts, and confidence intervals for time series An illustration of the method is given...

An empirical forecast accuracy comparison of the non-parametric method, known as multivariate Nearest Neighbor method, with parametric VAR modelling is conducted on the euro area GDP. Using both methods for nowcasting and forecasting the GDP, through the estimation of economic indicators plugged...

This paper develops the method for pricing bivariate contingent claims under General Autoregressive Conditionally Heteroskedastic (GARCH) process. In order to provide a general framework being able to accommodate skewness, leptokurtosis, fat tails as well as the time varying volatility that are...

The aim of this work is to bring an econometric approach upon the CO2 market. We identify the specificities of this market, and analyze the carbon as a commodity. We investigate the econometric particularities of CO2 prices behavior and their result of the calibration. We apprehend and explain...

Testing the fractionally integrated order of seasonal and nonseasonal unit roots is quite important for the economic and financial time series modeling. In this article, the widely used Robinson's (1994) test is applied to various well-known long memory models. Via Monte Carlo experiments, we...

This paper focuses on the use of dynamical chaotic systems in Economics and Finance. In these fields, researchers employ different methods from those taken by mathematicians and physicists. We discuss this point. Then, we present statistical tools and problems which are innovative and can be...

In this paper we study, using the sup LR test, the possibility of discrimination between two classes of models: the Markov switching models of Hamilton (1989) and the Threshold Auto-Regressive Models (TAR) of Lim and Tong (1980). This work is motivated by the fact that generally practicians use,...

In this paper, we discuss the class of Bilinear GATRCH (BL-GARCH) models which are capable of capturing simultaneously two key properties of non-linear time series : volatility clustering and leverage effects. It has been observed often that the marginal distributions of such time series have...

This paper analyzes the dynamics of the US inflation series using two classes of models : structural changes models and Long memory processes. For the first class, we use the Markov Switching (MS-AR) model of Hamilton (1989) and the Structural Change (SCH-AR) model using the sequential method...

Most financial time series exhibit seasonality, persistence (hyperbolic decay of the autocorrelation function), asymmetric behavior and leptokurtosis. In this paper, we introduce the stationary Seasonal Hyperbolic APARCH model, which can take into account the previous features. We then...