For decades, the academic literature has focused on three survey measures of expected inflation: the Livingston Survey, the Survey of Professional Forecasters, and the Michigan Survey. While these measures have been useful in developing models of forecasting inflation, the data are low frequency...

A unified quasi-maximum likelihood (QML) estimation theory for stationary and nonstationary simple Markov bilinear (SMBL) models is proposed. Such models may be seen as generalized random coefficient autoregressions (GRCA) in which the innovation and the random coefficient processes are fully...

Evaluating the treatment of missing values by SAS 6.12, the first target group is considered to be an uninitiated person like a physician who is doing his first real research in the frame of his doctoral thesis. Such a physician will easily come to wrong conclusions as the treatment of missing...

We propose a general class of non-linear mixed Poisson autoregressions whose form and parameters are periodic over time. Under a periodic contraction condition on the forms of the conditional mean, we show the existence of a unique nonanticipative solution to the model, which is strictly...

This book approaches the elementary statistical concepts. It presents also some statistical methods of collecting and analysis of data.

This study explores the volatility models and evaluates the quality of one-step ahead forecasts of volatility constructed by (1) GARCH, (2) TGARCH, (3) Risk metrics and (4) Historical volatility. Volatility forecasts suggest that TGARCH performs relatively best in term of MSPE, followed by...

This paper sets out some procedure allowing to deriving new information from the Business Tendency Surveys. Precisely, the volatility of respondents’ opinions will be computed that can be interpreted as a measure of radical (or true) uncertainty. This measure is strongly recommended by the...

In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986,1994) and Nelson (1990). First, we compare a stochastic volatility model relying on the Kalman filter to the conditional...