Searching for long memory effects in time series of central Europe stock market indices

This article deals with one of the important parts of applying chaos theory to financial and capital markets – namely searching for long memory effects in time series of financial instruments. Source data are daily closing prices of Central Europe stock market indices – Bratislava stock index (SAX),...

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Main Author: Luboš Střelec
Format: Article
Language:English
Published: Mendel University Press 2008-01-01
Series:Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
Subjects:
Online Access:https://acta.mendelu.cz/56/3/0187/
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author Luboš Střelec
author_facet Luboš Střelec
author_sort Luboš Střelec
collection DOAJ
description This article deals with one of the important parts of applying chaos theory to financial and capital markets – namely searching for long memory effects in time series of financial instruments. Source data are daily closing prices of Central Europe stock market indices – Bratislava stock index (SAX), Budapest stock index (BUX), Prague stock index (PX) and Vienna stock index (ATX) – in the period from January 1998 to September 2007. For analysed data R/S analysis is used to calculate the Hurst exponent. On the basis of the Hurst exponent is characterized formation and behaviour of analysed financial time series. Computed Hurst exponent is also statistical compared with his expected value signalling independent process. It is also operated with 5-day returns (i.e. weekly returns) for the purposes of comparison and identification nonperiodic cycles.
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spelling doaj.art-8e15a4a45c8f47aa9817a59603d4634c2022-12-22T03:33:55ZengMendel University PressActa Universitatis Agriculturae et Silviculturae Mendelianae Brunensis1211-85162464-83102008-01-0156318720010.11118/actaun200856030187Searching for long memory effects in time series of central Europe stock market indicesLuboš Střelec0Ústav statistiky a operačního výzkumu, Mendelova zemědělská a lesnická univerzita v Brně, Zemědělská 1, 613 00 Brno, Česká republikaThis article deals with one of the important parts of applying chaos theory to financial and capital markets – namely searching for long memory effects in time series of financial instruments. Source data are daily closing prices of Central Europe stock market indices – Bratislava stock index (SAX), Budapest stock index (BUX), Prague stock index (PX) and Vienna stock index (ATX) – in the period from January 1998 to September 2007. For analysed data R/S analysis is used to calculate the Hurst exponent. On the basis of the Hurst exponent is characterized formation and behaviour of analysed financial time series. Computed Hurst exponent is also statistical compared with his expected value signalling independent process. It is also operated with 5-day returns (i.e. weekly returns) for the purposes of comparison and identification nonperiodic cycles.https://acta.mendelu.cz/56/3/0187/Hurst exponentR/S analysisV-statisticlogarithmic ratiostock market index
spellingShingle Luboš Střelec
Searching for long memory effects in time series of central Europe stock market indices
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
Hurst exponent
R/S analysis
V-statistic
logarithmic ratio
stock market index
title Searching for long memory effects in time series of central Europe stock market indices
title_full Searching for long memory effects in time series of central Europe stock market indices
title_fullStr Searching for long memory effects in time series of central Europe stock market indices
title_full_unstemmed Searching for long memory effects in time series of central Europe stock market indices
title_short Searching for long memory effects in time series of central Europe stock market indices
title_sort searching for long memory effects in time series of central europe stock market indices
topic Hurst exponent
R/S analysis
V-statistic
logarithmic ratio
stock market index
url https://acta.mendelu.cz/56/3/0187/
work_keys_str_mv AT lubosstrelec searchingforlongmemoryeffectsintimeseriesofcentraleuropestockmarketindices