UNRAVELING FINANCIAL MARKET DYNAMICS: THE APPLICATION OF FRACTAL THEORY IN FINANCIAL TIME SERIES ANALYSIS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F25%3A50022281" target="_blank" >RIV/62690094:18450/25:50022281 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.worldscientific.com/doi/10.1142/S0218348X25500173" target="_blank" >https://www.worldscientific.com/doi/10.1142/S0218348X25500173</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1142/S0218348X25500173" target="_blank" >10.1142/S0218348X25500173</a>

Jazyk výsledku

angličtina

Název v původním jazyce

UNRAVELING FINANCIAL MARKET DYNAMICS: THE APPLICATION OF FRACTAL THEORY IN FINANCIAL TIME SERIES ANALYSIS

Popis výsledku v původním jazyce

Financial markets are characterized by complex and often unpredictable dynamics, presenting significant challenges for investors, analysts, and policymakers. In recent years, fractal theory has emerged as a powerful tool for understanding the intricate patterns and behaviors exhibited by financial time series data. This paper provides a comprehensive review of the application of fractal theory in financial time series analysis, examining its theoretical foundations, empirical applications, and practical implications. Through a synthesis of relevant literature, we explore the utility of fractal techniques such as fractal dimension estimation, detrended fluctuation analysis (DFA), and multifractal analysis in quantifying the long-range dependence, self-similarity, and scaling properties of financial time series. Additionally, we discuss the implications of fractal dynamics for risk management, portfolio optimization, and market microstructure analysis, highlighting opportunities for future research and innovation in this evolving field.

Název v anglickém jazyce

UNRAVELING FINANCIAL MARKET DYNAMICS: THE APPLICATION OF FRACTAL THEORY IN FINANCIAL TIME SERIES ANALYSIS

Popis výsledku anglicky

Financial markets are characterized by complex and often unpredictable dynamics, presenting significant challenges for investors, analysts, and policymakers. In recent years, fractal theory has emerged as a powerful tool for understanding the intricate patterns and behaviors exhibited by financial time series data. This paper provides a comprehensive review of the application of fractal theory in financial time series analysis, examining its theoretical foundations, empirical applications, and practical implications. Through a synthesis of relevant literature, we explore the utility of fractal techniques such as fractal dimension estimation, detrended fluctuation analysis (DFA), and multifractal analysis in quantifying the long-range dependence, self-similarity, and scaling properties of financial time series. Additionally, we discuss the implications of fractal dynamics for risk management, portfolio optimization, and market microstructure analysis, highlighting opportunities for future research and innovation in this evolving field.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

Fractals

ISSN

0218-348X

e-ISSN

1793-6543

Svazek periodika

33

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

SG - Singapurská republika

Počet stran výsledku

10

Strana od-do

"Article number: 2550017"

Kód UT WoS článku

001423945100001

EID výsledku v databázi Scopus

2-s2.0-85219413107