Forecast combination has been proven to be a very important technique to obtain accurate predictions for various applications in economics, finance, marketing and many other areas. In many applications, forecast errors exhibit heavy-tailed behaviors for various reasons. Unfortunately, to our...

This study is the first attempt to investigate both the linear and non-linear Granger causality between wavelet transformed spot and futures oil prices. Our findings consistently indicate bidirectional causality between the spot and futures oil markets at different time scales, under linear and...

This paper provides a survey of the recent literature dealing with I(2) variables in economic time series, that is, processes that require to be differenced twice in order to become stationary. With reference to particular models intuition is provided of why I(2) and polynomial cointegration are...

We propose marginal integration estimation and testing methods for the coefficients of varying coefficient multivariate regression model. Asymptotic distribution theory is developed for the estimation method which enjoys the same rate of convergence as univariate function estimation. For the...

The purpose of this work is to study the statistical properties of the MDD for stochastic processes characterized by the stylized facts of real financial time series. The numerical results obtained using a Monte Carlo code are firstly validated against the analytical predictions available within...

The statistical estimate of the branching ratio η of the Hawkes model, when fitted to windows of mid-price changes, has been reported to approach criticality (η = 1) as the fitting window becomes large. In this study -- using price changes from the EUR/USD currency pair traded on the...

In this paper I describe and apply the methods of Symbolic Time Series Analysis (STSA) to an experimental framework. The idea behind Symbolic Time Series Analysis is simple: the values of a given time series data are transformed into a finite set of symbols obtaining a finite string. Then, we...

This paper uses fractional integration methods to measure the degree of persistence in historical annual data on the world population over the period 1800-2016. The analysis is carried out for the original series, and also for its log transformation and its growth rate. The results indicate that...

This paper provides estimates of persistence in historical UK data on life expectancy applying fractional integration methods to both an annual series from 1842 to 2019 and a 5-year average from 1543 to 2019. The results indicate that the former exhibits an upward trend and is persistent but...

The traditional time series methodology requires at least a preliminary transformation of the data to get stationarity. On the other hand, robust Bayesian dynamic models (RBDMs) do not assume a regular pattern or stability of the underlying system but can include points of statement breaks. In...