Evidence for deterministic nonlinear dynamics in financial time series data

Michael Small; C. K. Tse

doi:10.1109/CIFER.2003.1196280

Evidence for deterministic nonlinear dynamics in financial time series data

Michael Small, C. K. Tse

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

Intra-day measurements of three time series (DJIA, gold fixings and USD-JPY exchange rates) are examined for evidence of deterministic nonlinear dynamics. Standard linear surrogate techniques and estimation of dynamic invariants demonstrate that linear noise models are insufficient to explain dynamic variability in intra-day returns. Therefore, the data may not be modeled as a monotonic nonlinear transformation of linearly filtered noise. Furthermore, a new nonlinear surrogate technique is employed to demonstrate that conditional heteroskedastic models are also insufficient to model this data. We conclude that the most likely model of the data is a nonlinear dynamical system driven by high dimensional dynamics (noise).

Original language	English
Title of host publication	2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Proceedings
Publisher	IEEE
Pages	339-346
Volume	2003-January
ISBN (Print)	0780376544
DOIs	https://doi.org/10.1109/CIFER.2003.1196280
Publication status	Published - Mar 2003
Externally published	Yes
Event	2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Hong Kong, China Duration: 20 Mar 2003 → 23 Mar 2003

Publication series

Name	IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)
Volume	2003-January

Conference

Conference	2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003
Place	China
City	Hong Kong
Period	20/03/03 → 23/03/03

Research Keywords

Chaos
Contamination
Data analysis
Exchange rates
Extraterrestrial measurements
Noise measurement
Nonlinear dynamical systems
Pollution measurement
Testing
Time measurement

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10.1109/CIFER.2003.1196280

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Small, M., & Tse, C. K. (2003). Evidence for deterministic nonlinear dynamics in financial time series data. In 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Proceedings (Vol. 2003-January, pp. 339-346). Article 1196280 (IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr); Vol. 2003-January). IEEE. https://doi.org/10.1109/CIFER.2003.1196280

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title = "Evidence for deterministic nonlinear dynamics in financial time series data",

abstract = "Intra-day measurements of three time series (DJIA, gold fixings and USD-JPY exchange rates) are examined for evidence of deterministic nonlinear dynamics. Standard linear surrogate techniques and estimation of dynamic invariants demonstrate that linear noise models are insufficient to explain dynamic variability in intra-day returns. Therefore, the data may not be modeled as a monotonic nonlinear transformation of linearly filtered noise. Furthermore, a new nonlinear surrogate technique is employed to demonstrate that conditional heteroskedastic models are also insufficient to model this data. We conclude that the most likely model of the data is a nonlinear dynamical system driven by high dimensional dynamics (noise).",

keywords = "Chaos, Contamination, Data analysis, Exchange rates, Extraterrestrial measurements, Noise measurement, Nonlinear dynamical systems, Pollution measurement, Testing, Time measurement",

author = "Michael Small and Tse, {C. K.}",

year = "2003",

month = mar,

doi = "10.1109/CIFER.2003.1196280",

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booktitle = "2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Proceedings",

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note = "2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 ; Conference date: 20-03-2003 Through 23-03-2003",

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Small, M & Tse, CK 2003, Evidence for deterministic nonlinear dynamics in financial time series data. in 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Proceedings. vol. 2003-January, 1196280, IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr), vol. 2003-January, IEEE, pp. 339-346, 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003, Hong Kong, China, 20/03/03. https://doi.org/10.1109/CIFER.2003.1196280

Evidence for deterministic nonlinear dynamics in financial time series data. / Small, Michael; Tse, C. K.
2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Proceedings. Vol. 2003-January IEEE, 2003. p. 339-346 1196280 (IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr); Vol. 2003-January).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Evidence for deterministic nonlinear dynamics in financial time series data

AU - Small, Michael

AU - Tse, C. K.

PY - 2003/3

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N2 - Intra-day measurements of three time series (DJIA, gold fixings and USD-JPY exchange rates) are examined for evidence of deterministic nonlinear dynamics. Standard linear surrogate techniques and estimation of dynamic invariants demonstrate that linear noise models are insufficient to explain dynamic variability in intra-day returns. Therefore, the data may not be modeled as a monotonic nonlinear transformation of linearly filtered noise. Furthermore, a new nonlinear surrogate technique is employed to demonstrate that conditional heteroskedastic models are also insufficient to model this data. We conclude that the most likely model of the data is a nonlinear dynamical system driven by high dimensional dynamics (noise).

AB - Intra-day measurements of three time series (DJIA, gold fixings and USD-JPY exchange rates) are examined for evidence of deterministic nonlinear dynamics. Standard linear surrogate techniques and estimation of dynamic invariants demonstrate that linear noise models are insufficient to explain dynamic variability in intra-day returns. Therefore, the data may not be modeled as a monotonic nonlinear transformation of linearly filtered noise. Furthermore, a new nonlinear surrogate technique is employed to demonstrate that conditional heteroskedastic models are also insufficient to model this data. We conclude that the most likely model of the data is a nonlinear dynamical system driven by high dimensional dynamics (noise).

KW - Chaos

KW - Contamination

KW - Data analysis

KW - Exchange rates

KW - Extraterrestrial measurements

KW - Noise measurement

KW - Nonlinear dynamical systems

KW - Pollution measurement

KW - Testing

KW - Time measurement

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U2 - 10.1109/CIFER.2003.1196280

DO - 10.1109/CIFER.2003.1196280

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0780376544

VL - 2003-January

T3 - IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)

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BT - 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Proceedings

PB - IEEE

T2 - 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003

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ER -

Small M, Tse CK. Evidence for deterministic nonlinear dynamics in financial time series data. In 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, CIFEr 2003 - Proceedings. Vol. 2003-January. IEEE. 2003. p. 339-346. 1196280. (IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, Proceedings (CIFEr)). doi: 10.1109/CIFER.2003.1196280

Evidence for deterministic nonlinear dynamics in financial time series data

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