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Randomized unit root processes for modelling and forecasting financial time series: Theory and applications
Author(s) -
Leybourne Stephen J.,
McCabe Brendan P. M.,
Mills Terence C.
Publication year - 1996
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/(sici)1099-131x(199604)15:3<253::aid-for622>3.0.co;2-c
Subject(s) - unit root , econometrics , context (archaeology) , series (stratigraphy) , computer science , economics , paleontology , biology
This paper considers the problems of statistically analysing the levels of financial time series rather than their differences, which are often equivalent to returns and which are traditionally analysed in econometric modelling. This focus on differences is a consequence of the inherent nonstationarity of the levels, and hence analysing the latter requires introducing an alternative framework for modelling nonstationary behaviour. We do this by considering randomized unit root processes, arguing that these can have a natural interpretation in the financial context. The paper thus develops methods for testing for randomized unit roots and for modelling such processes. It then applies these techniques to various financial time series, so as to ascertain their potential usefulness, particularly for forecasting.