Time Series Analysis, Cointegration, and Applications

Cointegration for Seasonal Time Series Processes

This paper examines types of cointegration for bivariate seasonal time series, namely seasonal cointegration, periodic cointegration and nonperiodic cointegration. The admissable form(s) for any cointegration is shown to depend crucially on the univariate unit root properties of the series. When both processes are (conventionally) integrated, only nonperiodic cointegration is possible. Periodic...

Theory and Applications for Time Series Analysis

We construct parametric and rank-based optimal tests for eigenvectors and eigenvalues of covariance or scatter matrices in elliptical families. The parametric tests extend the Gaussian likelihood ratio tests of Anderson (1963) and their pseudo-Gaussian robustifications by Davis (1977) and Tyler (1981, 1983), with which their Gaussian versions are shown to coincide, asymptotically, under Gaussia...

Fractional Integration and Cointegration in US Financial Time Series Data

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 d < 1, which implies mean reversion. The multivariate framework exploiting recent developments in fr...

Time - series Econometrics : Cointegration and Autoregressive Conditional Heteroskedasticity

Modelling Time Series Data of Monetary Aggregates Using I(2) and I(1) Cointegration Analysis

The objective of this paper is to consider methodology for modelling time series data of monetary aggregates such as monetary base and broad money. A brief review is made with regard to the likelihood-based cointegration analysis of I(2) (integrated of order 2) data and I(2)-to-I(1) transformations. The paper then investigates procedures for econometric modelling of monetary aggregates, which a...