In this paper we present several new ¯ndings on the NoVaS transformation approach for volatility forecasting introduced by Politis (2003a,b, 2007). In particular: (a) we present a new method for accurate volatility forecasting using NoVaS ; (b) we introduce a \time- varying" version of NoVaS...

We study the properties of a quasi-maximum likelihood (QML) for the parameters of a "weak" GARCH process obtained by contemporaneous aggregation of two independent "strong" GARCH processes. The inconsistency of the Gaussian quasi-likelihood estimator (QMLE) has already been reported by Nijman &...

Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of returns. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled...

Utilizing open-close returns, close-close returns and volume data, we examine the reaction of the Treasury futures market to the periodically scheduled announcements of prominent U.S. macroeconomic data. Heterogeneous persistence from scheduled news vs. non-scheduled news is revealed. Strong...

This note shows that a very simple model can generate returns that resemble most of the temporal and distributional behavior of long returns surprisingly well. The model is based on the stochastic unit root process introduced in Granger and Swanson (1997).