Fractal and Multifractal Analysis in Econometric Models and Empirical Finance

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Mathematical Physics".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 1388

Special Issue Editor


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Guest Editor
Department of Financial Mathematics, Gachon University, Seongnam 13120, Republic of Korea
Interests: multifractal analysis; economic finance; financial mathematics; machine learning

Special Issue Information

Dear Colleagues,

In an era of rapid global economic shifts, the imperative to model and gain profound insights into economic markets has never been more pressing. This Special Issue is expressly designed to meet this challenge by offering a platform for in-depth economic analysis, with a particular focus on the application of fractal and multifractal analysis.

Fractal and multifractal analysis represent cutting-edge tools for unraveling the intricate dynamics of financial markets, making them invaluable in the pursuit of a deeper understanding of economic systems. This exploration not only sheds light on the factors that underpin market stability and turbulence but also enriches our comprehension of economic cycles, trends, and risk factors.

Multifractal analysis, in particular, has gained prominence across various economic and financial domains. It empowers researchers to take a comprehensive approach to analyzing financial time series, market microstructure, asset price dynamics, and market efficiency. By applying multifractals, we can assess risk and model volatility and uncover intricate relationships within economic systems.

In our increasingly interconnected world, examining the global economy is more relevant than ever. This Special Issue seeks to delve into the multifaceted aspects of economic systems on a global scale, addressing the challenges and opportunities arising from a complex and interdependent world. It invites contributions that enhance our understanding of economic markets, providing fresh insights that can inform economic policy and decision-making in the dynamic global landscape.

In summary, this Special Issue harnesses the power of fractal and multifractal analysis to decode economic complexities, presenting a collaborative space for researchers and economists to advance our collective knowledge of the intricate and ever-evolving global economy.

Prof. Dr. Sun-Yong Choi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Fractal and Fractional is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multifractal analysis
  • hurst exponent
  • multiscale analysis
  • financial market efficiency
  • empirical finance

Published Papers (1 paper)

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Research

23 pages, 2519 KiB  
Article
Multifractal Detrended Cross-Correlations between Green Bonds and Commodity Markets: An Exploration of the Complex Connections between Green Finance and Commodities from the Econophysics Perspective
by Turker Acikgoz, Soner Gokten and Abdullah Bugra Soylu
Fractal Fract. 2024, 8(2), 117; https://doi.org/10.3390/fractalfract8020117 - 15 Feb 2024
Viewed by 1144
Abstract
Green bonds represent a compelling financial innovation that presents a financial perspective solution to address climate change and promote sustainable development. On the other hand, the recent process of financialisation of commodities disrupts the dynamics of the commodity market, increasing its correlation with [...] Read more.
Green bonds represent a compelling financial innovation that presents a financial perspective solution to address climate change and promote sustainable development. On the other hand, the recent process of financialisation of commodities disrupts the dynamics of the commodity market, increasing its correlation with financial markets and raising the risks associated with commodities. In this context, understanding the dynamics of the interconnectivity between green bonds and commodity markets is crucial for risk management and portfolio diversification. This study aims to reveal the multifractal cross-correlations between green bonds and commodities by employing methods from statistical physics. We apply multifractal detrended cross-correlation analysis (MFDCCA) to both return and volatility series, demonstrating that green bonds and commodities exhibit multifractal characteristics. The analysis reveals long-range power-law cross-correlations between these two markets. Specifically, volatility cross-correlations persist across various fluctuations, while return series display persistence in small fluctuations and antipersistence in large fluctuations. These findings carry significant practical implications for hedging and risk diversification purposes. Full article
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