Persistence in high frequency financial data: the case of the EuroStoxx 50 futures prices

Caporale, Guglielmo Maria; Plastun, Alex

doi:10.1080/23322039.2024.2302639

Cited by 2 publications

(1 citation statement)

References 35 publications

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“…To measure the degree of persistence R/S analysis is applied. The first is based on the following algorithm (see Caporale and Plastun, 2024 for additional details):…”

Section: Methodsmentioning

confidence: 99%

Transformation of the Ukrainian Stock Market: A Data Properties View

Plastun,

Hariaha,

Yatsenko

et al. 2024

Preprint

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This paper examines the transformation of the Ukrainian stock market by analyzing daily returns from the PFTS stock index spanning 1995-2022. Segmented into sub-periods, it tests the hypothesis that the market's efficiency has grown over time. Various data properties, including persistence, volatility, normality, and resistance to anomalies, are explored using different statistical techniques and methods. Volatility, indicated by standard deviation, exhibits a general decreasing trend, suggesting a shift towards a more efficient market. Returns show no significant differences across sub-periods, except for 2005-2007. R/S analysis indicates the decrease of persistence in the market: a trend towards increased efficiency. Normality tests support a normal distribution of daily returns throughout sub-periods. An analysis of anomalies reveals the market's resilience to day-of-the-week effects, with no specific trends observed. The results suggest the absence of serious changes in data properties in the Ukrainian stock market over the time, means evolutionary processes over 25 years can’t be clearly observed. Reforms and changes have had limited impact, justifying continued reform for the market's evolution.

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“…To measure the degree of persistence R/S analysis is applied. The first is based on the following algorithm (see Caporale and Plastun, 2024 for additional details):…”

Section: Methodsmentioning

confidence: 99%

Transformation of the Ukrainian Stock Market: A Data Properties View

Plastun,

Hariaha,

Yatsenko

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Transformation of the Ukrainian Stock Market: A Data Properties View

Plastun,

Hariaha,

Yatsenko

et al. 2024

JRFM

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This paper investigates the evolution of the Ukrainian stock market through an analysis of various data properties, including persistence, volatility, normality, and resistance to anomalies for the case of daily returns from the PFTS stock index spanning 1995–2022. Segmented into sub-periods, it aims to test the hypothesis that the market’s efficiency has increased over time. To do this different statistical techniques and methods are used, including R/S analysis, ANOVA analysis, regression analysis with dummy variables, t-tests, and others. The findings present a mixed picture: while volatility and persistence demonstrate a general decreasing trend, indicating a potential shift towards a more efficient market, normality tests reveal no discernible differences between analyzed periods. Similarly, the analysis of anomalies shows no specific trends in the market’s resilience to the day-of-the-week effect. Overall, the results suggest a lack of systematic changes in data properties in the Ukrainian stock market over time, possibly due to the country’s volatile conditions, including two revolutions, economic crises, the annexation of territories, and a Russian invasion leading to the largest war in Europe since WWII. The limited impact of reforms and changes justifies the need for continued market reform and evolution post-war.

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Persistence in high frequency financial data: the case of the EuroStoxx 50 futures prices

Cited by 2 publications

References 35 publications

Transformation of the Ukrainian Stock Market: A Data Properties View

Transformation of the Ukrainian Stock Market: A Data Properties View

Transformation of the Ukrainian Stock Market: A Data Properties View

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