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Determinism in Financial Time Series
"... Copyright c○2003 by the authors. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher bepress ..."
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Copyright c○2003 by the authors. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher bepress. Determinism in Financial Time Series The attractive possibility that financial indices may be chaotic has been the subject of much study. In this paper we address two specific questions: “Masked by stochasticity, do financial data exhibit deterministic nonlinearity?”, and “If so, so what?”. We examine daily returns from three financial indicators: the Dow Jones Industrial Average, the London gold fixings, and the USDJPY exchange rate. For each data set we apply surrogate data methods and nonlinearity tests to quantify determinism over a wide range of time scales (from 100 to 20,000 days). We find that all three time series are distinct from linear noise or conditional heteroskedastic models and that there therefore exists detectable deterministic nonlinearity that can potentially be exploited for prediction.
Extracting biochemical reaction kinetics from time series data
 In M. Gh. Negoita et al. (Eds.), KnowledgeBased Intelligent Information & Engineering Systems, Lecture Notes in Artificial Intelligence
, 2004
"... Abstract. We consider the problem of inferring kinetic mechanisms for biochemical reactions from time series data. Using a priori knowledge about the structure of chemical reaction kinetics we develop global nonlinear models which use elementary reactions as a basis set, and discuss model constructi ..."
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Abstract. We consider the problem of inferring kinetic mechanisms for biochemical reactions from time series data. Using a priori knowledge about the structure of chemical reaction kinetics we develop global nonlinear models which use elementary reactions as a basis set, and discuss model construction using topdown and bottomup approaches. 1
M: Equivalence between ’feeling the pulse’ on the human wrist and the pulse pressure wave at fingertip
 International Journal of Neural Systems
"... Feeling the pulse on the wrist is the regular diagnostic method in traditional Chinese medicine. However it is natural to ask whether there is any difference between feeling the pulse on the wrist or at any other part of the body: such as the fingertips at which it is easily measured by electronic d ..."
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Feeling the pulse on the wrist is the regular diagnostic method in traditional Chinese medicine. However it is natural to ask whether there is any difference between feeling the pulse on the wrist or at any other part of the body: such as the fingertips at which it is easily measured by electronic devices. We employ a series of neural networks to model blood pressure propagation from the wrist to the fingertip. In order to avoid the problem of overfitting we apply information theoretic criterion to determine the optimal model in these networks and then apply surrogate data method to the residuals in this model. We demonstrate the application of this method to recordings of human pulse in six subjects. Our result indicates that there is no significant difference between pulse waveform measure on the lateral arterial artery (wrist) and at the fingertip.
Using Surrogate Data to Test for Nonlinearity in Experimental Data
"... The technique of surrogate data provides has been used to test for membership of particular classes of linear systems. Existing algorithms provide nonparametric methods to generate surrogates similar to the data and consistent with a given hypothesis. These nonparametric methods allow a wide range ..."
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The technique of surrogate data provides has been used to test for membership of particular classes of linear systems. Existing algorithms provide nonparametric methods to generate surrogates similar to the data and consistent with a given hypothesis. These nonparametric methods allow a wide range of test statistics to be utilized. We suggest an obvious extension of this to classes of nonlinear parametric models. To do so it is necessary to restrict the statistics employed to a relatively broad class. We demonstrate that correlation dimension provides a suitable statistic and apply these methods, together with existing surrogate tests to respiratory data from sleeping infants. Although our data are clearly distinct from the different classes of linear systems we are unable to distinguish between our data and surrogates generated by nonlinear models. Hence we conclude that our data cannot be explained by linearly filtered noise but is consistent with the noisy periodic orbit of a nonl...
Optimal selection of embedding parameters for time series modelling
 European Conference on Circuits Theory and Design (European Circuit Society and the Institute of Electrical and Electronic Engineers; Krakow
, 2003
"... Abstract  Time delay embedding is the ¯rst step in reconstruction of deterministic nonlinear dynamics from a time series. Unfortunately, there is no generic way to select the best time delay embedding. We show that for time series modelling it is possible to apply information theoretic arguments ..."
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Abstract  Time delay embedding is the ¯rst step in reconstruction of deterministic nonlinear dynamics from a time series. Unfortunately, there is no generic way to select the best time delay embedding. We show that for time series modelling it is possible to apply information theoretic arguments which lead to optimal selection of embedding window. Our results show that selection of embedding dimension and embedding lag should be considered not as part of the embedding process but as part of the modelling procedure. Nonlinear time series modelling results show qualitative and quantitative improvement in both long term and short term dynamics. 1
An Empirical
 Investigation of International Asset Pricing, Review of Financial Studies
, 1989
"... evidences of a common multifractal signature in economic, biological and physical systems ..."
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evidences of a common multifractal signature in economic, biological and physical systems
Detecting determinism in time series data: When should we bother to build models
 In International Symposium on Nonlinear Theory and its Applications (NOLTA
, 2002
"... Nonlinear modeling routines are often applied in an effort to extract underlying determinism from time series data. The best of these methods perform well for short noisy time series when there is determinism in the underlying system. We show that nonlinear modeling does not distinguish between a ..."
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Nonlinear modeling routines are often applied in an effort to extract underlying determinism from time series data. The best of these methods perform well for short noisy time series when there is determinism in the underlying system. We show that nonlinear modeling does not distinguish between a static nonlinear transformation of linearly filtered noise and dynamic nonlinearity. To relieve this problem we recommend that surrogate data methods should be applied prior to nonlinear modeling, and the results of that analysis used to guide model selection. 1.
THE DANGER OF WISHING FOR CHAOS
"... With the discovery of chaos came the hope of finding simple models that would be capable of explaining complex phenomena. Numerous papers claimed to find lowdimensional chaos in a number of areas ranging from the brain to the stockmarket. Years later, many of these claims have been disproved and th ..."
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With the discovery of chaos came the hope of finding simple models that would be capable of explaining complex phenomena. Numerous papers claimed to find lowdimensional chaos in a number of areas ranging from the brain to the stockmarket. Years later, many of these claims have been disproved and the fantastic hopes pinned on chaos have been toned down as research with more realistic objectives follows. The difficulty in calculating reliable estimates of the correlation dimension and the maximal Lyapunov exponent, two of the hallmarks of chaos, are explored. Given that nonlinear dynamics is a relatively new and growing field of science, the need for statistical testing is greater than ever. Surrogate data provides one possible approach but great care is needed in generating relevant surrogates and in interpreting the results. Examples of misleading applications and challenges for the future of research in nonlinear dynamics are discussed.
Models of knowing and the investigation of dynamical systems
 for the RBF1 and L 10 Predictions of the NMR laser
, 1999
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Macromodeling of Digital I/O Ports for System EMC Assessment
 In Design, Automation and Test in Europe Conference and Exhibition, 2002. Proceedings
, 2002
"... behavioral models of digital integrated circuit input and output ports for EMC and signal integrity simulations. A practical modeling process is proposed and applied to some example devices. The modeling process is simple and efficient, and it yields models performing at a very high accuracy level. ..."
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behavioral models of digital integrated circuit input and output ports for EMC and signal integrity simulations. A practical modeling process is proposed and applied to some example devices. The modeling process is simple and efficient, and it yields models performing at a very high accuracy level.