Sub-sequence incidence analysis within series of Bernoulli trials: application in characterisation of time series dynamics

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Abstract

This paper presents a new and widely applicable nonparametric approach to the characterisation of time series dynamics. The approach involves analysis of the incidence of occurrence of patterns in the direction of movement of the series, and may readily be applied to time series data measured on any scale. The paper includes derivations of analytic forms for two (infinite) families of distributions under the null hypothesis of random behaviour, and of a useful analytic form for the generation of the moments of these distributions. The distributions are asymptotically normal, so allowing for straightforward application of the approach presented in the paper too long series of high frequency and/or extended time period data. Areas of application in finance and accounting are suggested.

LanguageEnglish
JournalThe European Journal of Finance
Early online date12 Apr 2019
DOIs
StatusE-pub ahead of print - 12 Apr 2019

Cite this

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title = "Sub-sequence incidence analysis within series of Bernoulli trials: application in characterisation of time series dynamics",
abstract = "This paper presents a new and widely applicable nonparametric approach to the characterisation of time series dynamics. The approach involves analysis of the incidence of occurrence of patterns in the direction of movement of the series, and may readily be applied to time series data measured on any scale. The paper includes derivations of analytic forms for two (infinite) families of distributions under the null hypothesis of random behaviour, and of a useful analytic form for the generation of the moments of these distributions. The distributions are asymptotically normal, so allowing for straightforward application of the approach presented in the paper too long series of high frequency and/or extended time period data. Areas of application in finance and accounting are suggested.",
author = "Richard Jackson",
year = "2019",
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language = "English",
journal = "The European Journal of Finance",
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