exchange rate. The separate estimation of long-run money demands leads to a "structural" error correction equation which allows …

dealing with more than one lag. When the mean has an additive structure, however, better estimation methods are available … estimation of the conditional mean, it is equally if not more important to measure the future risk of the series along with the … interpretation of each lagged value's influence on such a function. In this paper we consider the joint estimation of both the …

, and the Deutschmark-US dollar. The estimation results for both models show: (i) that the unrestricted model outperforms …

problem of online estimation of current values of w = w(T) and a = a(T) from the observations SI , ... ,ST. We propose an … adaptive method of estimation which does not use any information about time homogeneity of the obscured process. We apply this …

This paper offers a new approach for estimation and forecasting of the volatility of financial time series. No …. -- stochastic volatility model ; adaptive estimation ; local homogeneity …

We derive an asymptotic theory of nonparametric estimation for an nonlinear transfer function model Z(t) = f (Xt) + Wt … interpreted as a nonlinear cointegration type relationship, but we believe that our results have wider interest. The class of … properties f(x) are studied via a set of simulation experiments. -- cointegration ; nonstationary time series models ; null …

following the classical approach based on I(0) stationarity or I(1) cointegrating relationships, we use fractional integration/cointegration … three variables are I(1). But we only find cointegration in the presence of autocorrelated disturbances, which means that … opposed to classical cointegration, which implies long memory and slow reversion to equilibrium. This suggests that an …

the null hypothesis of no cointegration against alternatives which are fractionally cointegrated. Monte Carlo simulations … (EMH) ; Present Value (PV) models ; fractional cointegration …