Correlation dimension as a measure of stock market variability

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Correlation dimension as a measure of stock market variability

Popis výsledku v původním jazyce

Economical time series often show fractional behaviour. Since this type of data can be considered as a realisation of stochastic process with unknown prop- erties, it can be analysed with the tools of fractal geometry. In the particular case of stock market indices, one can investigate any individual index using state space re- construction according to Whitney theorem. The second possibility of the analysis is the study of development of a group of different indices describing the state of the market at a specific time. Subsequently, long-time stock market history is useful for the investigation of the states as vectors in Euclidean space. Their fractal nature can be studied using correlation dimension. The paper presents several approaches to its estimation and compares the results in terms of the individual stock market behaviour. As a referential technique, the classical approach using correlation sum is presented and its performance is discussed in the context of obtained results. Furthermore, the analysis is useful for the dependency analysis and measure of predictability of time series.

Název v anglickém jazyce

Correlation dimension as a measure of stock market variability

Popis výsledku anglicky

Economical time series often show fractional behaviour. Since this type of data can be considered as a realisation of stochastic process with unknown prop- erties, it can be analysed with the tools of fractal geometry. In the particular case of stock market indices, one can investigate any individual index using state space re- construction according to Whitney theorem. The second possibility of the analysis is the study of development of a group of different indices describing the state of the market at a specific time. Subsequently, long-time stock market history is useful for the investigation of the states as vectors in Euclidean space. Their fractal nature can be studied using correlation dimension. The paper presents several approaches to its estimation and compares the results in terms of the individual stock market behaviour. As a referential technique, the classical approach using correlation sum is presented and its performance is discussed in the context of obtained results. Furthermore, the analysis is useful for the dependency analysis and measure of predictability of time series.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Mathematical Methods in Economics MME 2017

ISBN

978-80-7435-678-0

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

119-124

Název nakladatele

Univerzita Hradec Králové

Místo vydání

Hradec Králové

Místo konání akce

Hradec Králové

Datum konání akce

13. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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