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IJFS
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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: 30 September 2026 | Viewed by 9891

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 250 words) can be sent to the Editorial Office for assessment.

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 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 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 (7 papers)

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Research

46 pages, 6524 KB  
Article
A Hybrid Genetic Algorithm with Learning-to-Rank-to-Optimization for US Equity Portfolio Construction
by Ferdinantos Kottas
Int. J. Financial Stud. 2026, 14(4), 95; https://doi.org/10.3390/ijfs14040095 - 4 Apr 2026
Viewed by 544
Abstract
This study develops and evaluates an equity selection pipeline that converts quarterly fundamentals into a monthly frequency, constructs profitability, leverage, liquidity, and growth characteristics, and learns a linear ranking model via a genetic algorithm (GA). The GA is trained to maximize either (i) [...] Read more.
This study develops and evaluates an equity selection pipeline that converts quarterly fundamentals into a monthly frequency, constructs profitability, leverage, liquidity, and growth characteristics, and learns a linear ranking model via a genetic algorithm (GA). The GA is trained to maximize either (i) mean monthly NDCG@30 using 12-tile relevance labels or (ii) mean monthly Spearman information coefficient (IC). The learned ranker is tested out-of-sample using monthly forward returns, benchmarked against the S&P 500, with different types of allocation weights, and further evaluated under sector concentration limits. In the last layer, the monthly-selected stock universe is used in a daily dynamic allocation which is solved by the penalized Max-Sharpe or Min-Variance optimization problems under only long positions and transaction fees. Performance is examined across Pre-COVID, COVID, Post-COVID (Train), and Final Test regimes, demonstrating how ranking objectives and diversification constraints impact performance and stability. Results show that TTM-based accounting signals, when optimized through genetic learning and disciplined allocation, yield economically meaningful stock selection and robust portfolio performance across market regimes. Full article
(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
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18 pages, 676 KB  
Article
The Integration-Contagion Paradox: Global Linkages and Crisis Transmission in South Asian Stock Markets
by Dinesh Gajurel and Bharat Singh Thapa
Int. J. Financial Stud. 2026, 14(4), 86; https://doi.org/10.3390/ijfs14040086 - 2 Apr 2026
Viewed by 745
Abstract
This study examines financial integration and contagion across South Asia’s emerging and frontier markets during the 2001–2013 period, encompassing both the global financial and Eurozone crises. Employing a multi-factor asset pricing model within an EGARCH framework, we disentangle systematic global exposures from idiosyncratic [...] Read more.
This study examines financial integration and contagion across South Asia’s emerging and frontier markets during the 2001–2013 period, encompassing both the global financial and Eurozone crises. Employing a multi-factor asset pricing model within an EGARCH framework, we disentangle systematic global exposures from idiosyncratic shocks originating in the U.S. and Eurozone. By formally testing for structural changes in both mean returns and conditional variance, we uncover a striking “integration-contagion paradox.” While frontier markets (Bangladesh, Nepal) appear segmented from global pricing signals in tranquil times, they remain acutely susceptible to second-moment volatility contagion during stress periods. In contrast, India exhibits strong systematic return integration yet remains relatively insulated from volatility cascades. These results challenge the conventional view that financial segmentation offers a robust shield against systemic risk, revealing that a lack of global integration does not immunize markets against the transmission of global uncertainty. Full article
(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
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25 pages, 376 KB  
Article
Reconceptualizing Central Bank Transparency: A Multidimensional Index and Its Implications for International Equity Portfolio Allocation
by Sana Bhiri and Houda BenMabrouk
Int. J. Financial Stud. 2026, 14(3), 51; https://doi.org/10.3390/ijfs14030051 - 1 Mar 2026
Viewed by 677
Abstract
This paper examines the influence of Monetary Policy Transparency on Foreign Equity Portfolio Allocation by addressing the informational frictions that shape cross-border investment in Financial Markets. Building on recent developments in central bank communication, we construct a multidimensional measure of Monetary Policy Transparency [...] Read more.
This paper examines the influence of Monetary Policy Transparency on Foreign Equity Portfolio Allocation by addressing the informational frictions that shape cross-border investment in Financial Markets. Building on recent developments in central bank communication, we construct a multidimensional measure of Monetary Policy Transparency that extends traditional frameworks by incorporating Accounting Information Transparency and Financial Stability Transparency. This enhanced index provides a more comprehensive representation of the informational environment faced by foreign investors. Using a panel of developed and emerging economies over a twenty-year period, the empirical analysis combines OLS and system GMM estimations to account for endogeneity, dynamic effects, and unobserved heterogeneity. The results indicate that higher levels of Monetary Policy Transparency significantly increase the attractiveness of domestic equity markets to foreign investors, with heterogeneous effects across country groups linked to differences in institutional credibility and financial integration. Overall, the findings highlight multidimensional transparency as a key determinant of Foreign Equity Portfolio Allocation, underscoring the strategic importance of Accounting Information Transparency and Financial Stability Transparency in shaping foreign equity portfolio allocation. Full article
(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
21 pages, 309 KB  
Article
Online Search Activity and Market Reaction to Earnings Announcements
by Saurabh Ahluwalia
Int. J. Financial Stud. 2026, 14(2), 33; https://doi.org/10.3390/ijfs14020033 - 3 Feb 2026
Viewed by 1085
Abstract
This paper leverages Google Trends search volume data from 2004 to 2008 as a proxy for investor information demand. The analysis documents that greater search activity prior to earnings announcements is positively associated with future market reaction to earnings announcements, pre-earnings announcement drift, [...] Read more.
This paper leverages Google Trends search volume data from 2004 to 2008 as a proxy for investor information demand. The analysis documents that greater search activity prior to earnings announcements is positively associated with future market reaction to earnings announcements, pre-earnings announcement drift, and buying pressure. The results are consistent with investors gathering value-relevant information through online research, which is subsequently incorporated into prices through trading around earnings announcements. Notably, search volume is positively associated with market reaction to earnings announcements and pre-announcement drifts for more obscure firms where data is scarce. Overall, this paper provides large-sample evidence validating theoretical models where dispersed private information is incorporated into stock prices. The findings suggest that broader data access may facilitate pricing efficiency by promoting more informed market participation. Full article
(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
22 pages, 852 KB  
Article
Digital Financial Literacy and Investment Grip: A Study of Japanese Active Investors
by Aliyu Ali Bawalle, Sumeet Lal, Mostafa Saidur Rahim Khan and Yoshihiko Kadoya
Int. J. Financial Stud. 2026, 14(2), 25; https://doi.org/10.3390/ijfs14020025 - 27 Jan 2026
Viewed by 1589
Abstract
Investors’ ability to retain investments during bearish and uncertain market periods is a crucial behavioral trait for long-term wealth accumulation and reduces market instability. Nevertheless, little is understood about how digital financial literacy (DFL) shapes the capacity of increasingly digitalized financial environments. This [...] Read more.
Investors’ ability to retain investments during bearish and uncertain market periods is a crucial behavioral trait for long-term wealth accumulation and reduces market instability. Nevertheless, little is understood about how digital financial literacy (DFL) shapes the capacity of increasingly digitalized financial environments. This study investigates the links between DFL and investment grip among Japanese active investors—defined here, following conventional Japanese regulatory and research practice, as individuals who maintain a securities account and have engaged with an online brokerage within the past year—building on several theoretical perspectives from behavioral science. Using survey data from 149,261 individuals with an active account at Rakuten Securities, we estimated ordered probit regression models as the main specification. The findings showed a strong positive association between DFL and investment grip, even after accounting for demographic, socioeconomic, as well as cognitive attributes. These results are supported by robustness tests employing a probit model with a binary outcome. The sample consists exclusively of digitally active retail investors; the findings are therefore most directly applicable to this subpopulation. Overall, the evidence suggests that DFL fosters investors’ capacity to endure market volatility by promoting rational decision-making and reducing panic-driven selloffs. This study offers new empirical findings that will help promote financial resilience in technology-driven markets. Full article
(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
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21 pages, 365 KB  
Article
Quarterly vs. Semiannual Reporting: A Cross-Market Analysis of Earnings Announcement Reactions in the US and Europe
by Mark A. Ritter and Yusuf J. Ugras
Int. J. Financial Stud. 2025, 13(4), 207; https://doi.org/10.3390/ijfs13040207 - 5 Nov 2025
Viewed by 2293
Abstract
This study re-examines the ongoing debate over corporate disclosure frequency amid renewed calls to replace quarterly with semiannual reporting in U.S. markets. While traditional theories hold that frequent disclosure enhances informational efficiency by reducing asymmetry, emerging evidence highlights trade-offs involving managerial myopia, earnings [...] Read more.
This study re-examines the ongoing debate over corporate disclosure frequency amid renewed calls to replace quarterly with semiannual reporting in U.S. markets. While traditional theories hold that frequent disclosure enhances informational efficiency by reducing asymmetry, emerging evidence highlights trade-offs involving managerial myopia, earnings management, and heightened short-term volatility. Using data from 2007 to 2024, the study compares Dow Jones Industrial Average firms, which report quarterly, with STOXX 50 firms, which report semiannually, to assess how disclosure cadence affects market reactions to earnings news The methodology involves identifying volatility regimes using Self-Exciting Threshold Autoregressive (SETAR) models, estimating dynamic betas with the GARCH(1,1) model, and analyzing shock transmission through vector autoregressions with cumulative impulse response functions (CIRFs). The results show that quarterly reporters exhibit larger immediate price reactions but faster normalization, implying that more frequent reporting accelerates information assimilation while amplifying contemporaneous volatility. Sectoral heterogeneity is pronounced: cyclical industries display higher beta volatility and steeper, but shorter-lived responses, whereas defensive stocks exhibit smoother convergence. These findings suggest that disclosure frequency influences both the intensity and duration of information shocks, providing insights for regulators who aim to balance transparency, market efficiency, and reporting costs across varying volatility and sectoral environments. Full article
(This article belongs to the Special Issue Stock Market Developments and Investment Implications)
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
Cited by 2 | Viewed by 2183
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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