Over recent years, several nonlinear time series models have been proposed in the literature. One model that has found a large number of successful applications is the threshold autoregressive model (TAR). The TAR model is a piecewise linear process whose central idea is to change the parameters...

In this paper we examine the forecast accuracy of linear autoregressive, smooth transition autoregressive (STAR), and neural network (NN) time series models for 47 monthly macroeconomic variables of the G7 economies. Unlike previous studies that typically consider multiple but fixed model...

This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets might be efficient) or alternatively I(d) with...

This paper examines the PPP hypothesis analysing the behaviour of the real exchange rates vis-à-vis the US dollar for four major currencies (namely, the Canadian dollar, the euro, the Japanese yen and the British pound). An innovative approach based on fractional integration in a multivariate...

This paper analyses the stochastic behaviour of Private Equity returns (a measure of profitability) applying fractional integration methods to an extensive dataset including quarterly data spanning the last four decades for various geographical areas (US, Europe, Asia/Pacific, the Rest of the...

This paper investigates the degree of persistence of market fear. Specifically, two different long-memory approaches (R/S analysis with the Hurst exponent method and fractional integration) are used to analyse persistence of the VIX index over the sample period 2004-2016, as well as some...

This paper investigates the degree of persistence of market fear. Specifically, two different long-memory approaches (R/S analysis with the Hurst exponent method and fractional integration) are used to analyse persistence of the VIX index over the sample period 2004-2016, as well as some...

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume that both the number of covariates in the model and the number of candidate variables can increase with the sample size (polynomially or geometrically). In other...

This paper examines the degree of persistence in UK inflation by applying long-memory methods to historical data that span the period from 1660 to 2016. Specifically, we use both parametric and non-parametric fractional integration techniques, that are more general than those based on the...

This paper examines the degree of persistence in UK inflation by applying long-memory methods to historical data that span the period from 1660 to 2016. Specifically, we use both parametric and non-parametric fractional integration techniques, that are more general than those based on the...