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Advisor(s)
Abstract(s)
The goal of this study is the analysis of
the dynamical properties of financial data series from
worldwide stock market indexes during the period
2000–2009. We analyze, under a regional criterium,
ten main indexes at a daily time horizon. The methods
and algorithms that have been explored for the
description of dynamical phenomena become an effective
background in the analysis of economical data.
We start by applying the classical concepts of signal
analysis, fractional Fourier transform, and methods of
fractional calculus. In a second phase we adopt the
multidimensional scaling approach. Stock market indexes
are examples of complex interacting systems for
which a huge amount of data exists. Therefore, these
indexes, viewed from a different perspectives, lead to
new classification patterns.
Description
Keywords
Financial data series Fractional Fourier transform Multidimensional scaling Fractional calculus