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IJFS
Special Issues
Stock Market Developments and Investment Implications
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Stock Market Developments and Investment Implications

A special issue of International Journal of Financial Studies (ISSN 2227-7072).

Deadline for manuscript submissions: 31 January 2026 | Viewed by 420

Special Issue Editor

Prof. Dr. Khelifa Mazouz

E-Mail Website
Guest Editor
Cardiff Business School, Cardiff University, Cardiff CF10 3EU, UK
Interests: capital markets; asset pricing; international finance; corporate finance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The structure, behavior, and volatility of global stock markets continue to evolve in response to macroeconomic, technological, and geopolitical shifts. These ongoing developments present both challenges and opportunities for investors, regulators, and researchers seeking to understand market dynamics and make informed investment decisions.

This Special Issue of the International Journal of Financial Studies (IJFS) invites high-quality theoretical and empirical contributions that explore recent stock market developments and their implications for investment strategies, asset pricing, portfolio management, and financial regulation.

We seek original research that enhances our understanding of how modern stock markets operate under dynamic conditions and how investors respond to changing risks, innovations, and informational environments.

Topics of Interest

Relevant topics for submission include, but are not limited to, the following:

  • Market structure evolution and trading mechanisms;
  • Stock market volatility, anomalies, and market efficiency;
  • Behavioral and sentiment-driven market effects;
  • Impacts of algorithmic and high-frequency trading;
  • ESG investing and the integration of sustainability factors into equity markets;
  • The role of financial technologies and digital platforms in shaping investment behavior;
  • Monetary policy, inflation expectations, and equity market reactions;
  • Cross-border capital flows and emerging market dynamics;
  • Portfolio diversification and risk management in volatile environments;
  • Asset pricing innovations and empirical testing of financial models.

We welcome both single-country and cross-country studies, as well as research employing novel datasets or methodologies.

Prof. Dr. Khelifa Mazouz
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. International Journal of Financial Studies is an international peer-reviewed open access quarterly 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 1800 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

  • stock market volatility
  • investment strategies
  • asset pricing models
  • behavioral finance
  • algorithmic and high-frequency trading
  • ESG investing
  • financial technology (FinTech)
  • market efficiency
  • portfolio management
  • cross-border capital flows

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

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Research

18 pages, 1838 KB  
Article
Quantitative Modeling of Speculative Bubbles, Crash Dynamics, and Critical Transitions in the Stock Market Using the Log-Periodic Power-Law Model
by Avi Singh, Rajesh Mahadeva, Varun Sarda and Amit Kumar Goyal
Int. J. Financial Stud. 2025, 13(4), 195; https://doi.org/10.3390/ijfs13040195 - 17 Oct 2025
Viewed by 128
Abstract
The global economy frequently experiences cycles of rapid growth followed by abrupt crashes, challenging economists and analysts in forecasting and risk management. Crashes like the dot-com bubble crash and the 2008 global financial crisis caused huge disruptions to the world economy. These crashes [...] Read more.
The global economy frequently experiences cycles of rapid growth followed by abrupt crashes, challenging economists and analysts in forecasting and risk management. Crashes like the dot-com bubble crash and the 2008 global financial crisis caused huge disruptions to the world economy. These crashes have been found to display somewhat similar characteristics, like rapid price inflation and speculation, followed by collapse. In search of these underlying patterns, the Log-Periodic Power-Law (LPPL) model has emerged as a promising framework, capable of capturing self-reinforcing dynamics and log-periodic oscillations. However, while log-periodic structures have been tested in developed and stable markets, they lack validation in volatile and developing markets. This study investigates the applicability of the LPPL framework for modeling financial crashes in the Brazilian stock market, which serves as a representative case of a volatile market, particularly through the Bovespa Index (IBOVESPA). In this study, daily data spanning 1993 to 2025 is analyzed to model pre-crash oscillations and speculative bubbles for five major market crashes. In addition to the traditional LPPL model, autoregressive residual analysis is incorporated to account for market noise and improve predictive accuracy. The results demonstrate that the enhanced LPPL model effectively captures pre-crash oscillations and critical transitions, with low error metrics. Eigenstructure analysis of the Hessian matrices highlights stiff and sloppy parameters, emphasizing the pivotal role of critical time and frequency parameters. Overall, these findings validate LPPL-based nonlinear modeling as an effective approach for anticipating speculative bubbles and crash dynamics in complex financial systems. Full article
(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
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