Empirical evidence from time series methods which assume the usual I(0)/I(1) paradigm suggests that the efficient market hypothesis, stating that spot and futures prices of a commodity should cointegrate with a unit slope on futures prices, does not hold. However, these statistical methods are...

In this paper we analyze the limiting properties of the estimated parameters in a general class of asymmetric volatility models which are closely related to the traditional exponential GARCH model. The new representation has three main advantages over the traditional EGARCH: (1) It allows a much...

We suggest improved tests for cointegration rank in the vector autoregressive (VAR) model and develop asymptotic distribution theory and local power results. The tests are (quasi-)likelihood ratio tests based on a Gaussian likelihood, but of course the asymptotic results apply more generally....

This paper examines the limiting properties of the estimated parameters in the random field regression model recently proposed by Hamilton (Econometrica, 2001). Though the model is parametric, it enjoys the flexibility of the nonparametric approach since it can approximate a large collection of...

This paper proposes a sequential procedure to determine the common cointegration rank of panels of cointegrated VARs. It shows how a panel of cointegrated VARs can be transformed in a set of independent individual models. The likelihood function of the transformed panel is the sum of the...

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...

A review is given of parametric estimation methods for discretely sampled multivariate diffusion processes. The main focus is on estimating functions and asymptotic results. Maximum likelihood estimation is briefly considered, but the emphasis is on computationally less demanding martingale...

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...

A general theory of efficient estimation for ergodic diffusions sampled at high fre- quency is presented. High frequency sampling is now possible in many applications, in particular in finance. The theory is formulated in term of approximate martingale estimating functions and covers a large...