Estimation in nonlinear time series models has mainly been performed by least squares or maximum likelihood (ML) methods. The paper suggests and studies the performance of generalized method of moments (GMM) and indirect estimators for the autoregressive asymmetric moving average model. Both...

The impact of news of the Moscow and New York stock market exchanges on the <p> returns and volatilities of the Baltic state stock market indices is studied using daily <p> return data for the period of 2000-2005. A nonlinear time series model that accounts <p> for asymmetries in the conditional mean and...</p></p></p>

Forecasting using factor models based on large data sets have received ample attention due to the models’ ability to increase forecast accuracy with respect to a range of key macroeconomic variables in the US and the UK. However, forecasts based on such factor models do not uniformly...

This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the...

The paper discusses the latest economic crisis and the public policies used to mitigate the recession and improve the economic growth. The current target rate (monetary policy) is closed to zero since December 2008 with a new experimental policy (“quantitative easing”) to stimulate...

In this paper, the results of seasonal modeling of Sokoto monthly average temperature have been obtained using seasonal autoregressive integrated moving average modeling approach. Based on this seasonal modeling analysis, we conclude that, the best seasonal model among the models that are...

We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail, with...

We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail, with...

In this paper we use the approximate bias expressions developed in Yu (2012) and Bao et al. (2013) to improve the testing of the ordinary least squares or quasi-maximum likelihood estimator of the mean reversion parameter in continuous time models. We follow the approach given in Iglesias and...

The price adjustment coefficient model of Amihud and Mendelson (1987) is shown to be suitable for estimation by the Kalman filter. A techique that, under some commonly used conditions, is asymptotically efficient. By Monte Carlo simulations it is shown that both bias and mean squared error are...