Fractal Analysis in Sustainable Finance: Understanding Market Complexity

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

Deadline for manuscript submissions: 28 February 2027 | Viewed by 410

Special Issue Editors


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Guest Editor
Institute of Economic Sciences, 11000 Belgrade, Serbia
Interests: economics; sustainable development macroeconomics; fractal analysis; green financial markets

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Guest Editor
Institute of Economic Sciences, Zmaj Jovina 12, 11000 Belgrade, Serbia
Interests: nonlinear market dynamics; modeling green financial instruments; environmental econometrics: multifractal and entropy-based methods

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Guest Editor
Federal Institute of Education Science and Technology of Paraíba (IFPB), Patos 58700-030, Brazil
Interests: probability; mathematical statistics; statistical physics; applied probability; applied statistics; applied mathematics; information theory; multifractal analysis; data analysis; time series analysis
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Special Issue Information

Dear Colleagues,

Sustainable finance is undergoing rapid transformation driven by climate transition, energy restructuring, digital innovation, and geopolitical instability. Green bonds, ESG-linked assets, renewable energy markets, and climate-sensitive investments increasingly exhibit multiscale, nonlinear, and memory-dependent behavior that fundamentally challenges traditional equilibrium-based models. These markets display scaling laws, long-range dependence, volatility clustering, and regime-switching dynamics characteristic of complex systems, and these behaviors may differ meaningfully from their conventional counterparts in ways that standard financial theory cannot adequately capture.

Fractional calculus and fractal analysis provide rigorous mathematical frameworks for modeling such phenomena. Multifractal methods, fractional stochastic processes, entropy-based quantifiers, chaos theory, and information-theoretic measures enable the characterization of persistence structures, anomalous diffusion, cross-market dependence, and systemic shocks specific to sustainable financial systems. As green and climate-aligned markets mature and become increasingly intertwined with energy and environmental dynamics, these tools are becoming essential for capturing their distinctive complexity and improving predictability and risk assessment.

This Special Issue will advance theoretical developments and empirical applications of fractional and fractal methodologies within sustainable financial systems, with particular emphasis on understanding how complexity in green and climate-sensitive markets compares to, interacts with, and diverges from conventional financial behavior. We welcome original research articles and review papers addressing, but not limited to, the following topics:

  • Fractional differential and fractional-order modeling in sustainable finance and energy–finance systems;
  • Multifractal analysis of green, ESG, and conventional financial assets;
  • Comparative complexity of sustainable versus traditional financial markets;
  • Multiscale cross-dependence across energy, climate, and financial markets;
  • Fractional stochastic processes and memory-driven dynamics in ESG and climate-aligned markets;
  • Scaling behavior and anomalous diffusion in sustainable financial time series;
  • Entropy and information-theoretic measures of efficiency and predictability in green markets;
  • Nonlinear dynamics, chaos, and regime-switching in sustainability-driven market stress;
  • Fractal and fractional modeling of green cryptocurrencies and ESG-linked assets;
  • Machine learning and AI for detecting fractal structures in sustainable financial systems;
  • AI and data-driven learning of fractal features and fractional dynamics in sustainable contexts;
  • Fractional and multifractal methods for portfolio construction and risk management in green finance.

We particularly encourage contributions that enhance mathematical rigor while providing insights into systemic risk, resilience, and multiscale financial complexity in the context of sustainability transitions, as well as those that use fractional and fractal tools to shed new light on what makes sustainable finance structurally distinct.

Dr. Petar Mitić
Dr. Milena Kojic
Prof. Dr. Fernando Henrique Antunes De Araújo
Guest Editors

Manuscript Submission Information

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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

  • fractional calculus
  • fractal analysis
  • multifractal analysis
  • fractional stochastic processes
  • long-range dependence
  • entropy-based financial modeling
  • sustainable finance
  • market complexity

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Published Papers (1 paper)

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Research

21 pages, 3656 KB  
Article
Response of Green Bonds and Sustainable Equity Markets to Crisis Regimes: A Dynamic Multifractal Efficiency Assessment
by Fernando Henrique Antunes de Araujo, Milena Kojić and Petar Mitić
Fractal Fract. 2026, 10(6), 393; https://doi.org/10.3390/fractalfract10060393 - 8 Jun 2026
Viewed by 128
Abstract
This article examines whether the informational efficiency of green bonds and sustainability-oriented equity indices changes across crisis regimes. Methods: We analyze the S&P Green Bond Index and eight S&P sustainable equity indices from 16 February 2016 to 10 November 2025 using static and [...] Read more.
This article examines whether the informational efficiency of green bonds and sustainability-oriented equity indices changes across crisis regimes. Methods: We analyze the S&P Green Bond Index and eight S&P sustainable equity indices from 16 February 2016 to 10 November 2025 using static and rolling-window multifractal detrended fluctuation analysis. Rolling inefficiency, defined as the absolute deviation of the singularity-spectrum peak from 0.5, is then modelled with crisis-regime indicators, asset effects, dependence-robust inference, and window-level risk controls. Results: The S&P Green Bond Index remains among the most efficient and least volatile assets in the sample. Crisis-labelled windows display higher multifractal inefficiency than the pre-COVID benchmark, although the robustness checks show that part of the raw effect is transmitted through volatility and tail-risk conditions. Conclusions: Sustainable-finance efficiency is nonlinear and regime dependent, and the evidence is interpreted as a conditional association rather than causal identification. Green bonds are comparatively resilient, but not informationally invariant during systemic, geopolitical, and policy-driven stress. Full article
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