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Authors
Advisor(s)
Abstract(s)
This paper presents a novel method for the
analysis of nonlinear financial and economic systems.
The modeling approach integrates the classical concepts
of state space representation and time series regression.
The analytical and numerical scheme leads
to a parameter space representation that constitutes a
valid alternative to represent the dynamical behavior.
The results reveal that business cycles can be clearly
revealed, while the noise effects common in financial
indices can elegantly be filtered out of the results.
Description
Keywords
Time series Complex dynamics Financial analysis State space Trendlines
