On testing for nonlinear dependence and chaos in financial time series data

Aydin Cecen; Ahmet Ugur

On testing for nonlinear dependence and chaos in financial time series data

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

The paper is aimed at highlighting some of the pitfalls of empirical analysis in complex dynamics. Two examples of high frequency financial time series data analysis are provided in order to investigate the characteristics of the data generating processes involved and to illustrate the difficulties encountered in numerical analyses.

Original language	English
Pages (from-to)	203-208
Number of pages	6
Journal	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume	1
State	Published - 2005
Event	IEEE Systems, Man and Cybernetics Society, Proceedings - 2005 International Conference on Systems, Man and Cybernetics - Waikoloa, HI, United States Duration: Oct 10 2005 → Oct 12 2005

Keywords

BDSL test
Chaos
Correlation dimension
Lyapunov exponents
Self similarity

Cite this

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title = "On testing for nonlinear dependence and chaos in financial time series data",

abstract = "The paper is aimed at highlighting some of the pitfalls of empirical analysis in complex dynamics. Two examples of high frequency financial time series data analysis are provided in order to investigate the characteristics of the data generating processes involved and to illustrate the difficulties encountered in numerical analyses.",

keywords = "BDSL test, Chaos, Correlation dimension, Lyapunov exponents, Self similarity",

author = "Aydin Cecen and Ahmet Ugur",

year = "2005",

language = "English",

volume = "1",

pages = "203--208",

journal = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",

issn = "1062-922X",

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T1 - On testing for nonlinear dependence and chaos in financial time series data

AU - Cecen, Aydin

AU - Ugur, Ahmet

PY - 2005

Y1 - 2005

N2 - The paper is aimed at highlighting some of the pitfalls of empirical analysis in complex dynamics. Two examples of high frequency financial time series data analysis are provided in order to investigate the characteristics of the data generating processes involved and to illustrate the difficulties encountered in numerical analyses.

AB - The paper is aimed at highlighting some of the pitfalls of empirical analysis in complex dynamics. Two examples of high frequency financial time series data analysis are provided in order to investigate the characteristics of the data generating processes involved and to illustrate the difficulties encountered in numerical analyses.

KW - BDSL test

KW - Chaos

KW - Correlation dimension

KW - Lyapunov exponents

KW - Self similarity

UR - http://www.scopus.com/inward/record.url?scp=27944434181&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:27944434181

VL - 1

SP - 203

EP - 208

JO - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

JF - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

SN - 1062-922X

Y2 - 10 October 2005 through 12 October 2005

ER -

On testing for nonlinear dependence and chaos in financial time series data

Abstract

Keywords

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