Volatility on stock exchanges and its impact on transformations in the financial services market

doi:10.26565/2786-4995-2025-3-06

Serhii Zadvornykh Private Higher Education Institution “Rauf Ablyazov East European University” https://orcid.org/0000-0002-7025-4116

DOI: https://doi.org/10.26565/2786-4995-2025-3-06

Keywords: volatility, stock market, risk management, digital technologies, geopolitical risks, machine learning, Big Data, financial services market, analytics, transformations

Abstract

In modern global economy, stock market volatility has become one of the decisive factors shaping the financial services market. Exchange rate fluctuations not only affect asset valuation, but also investment decisions, risk management mechanisms, and the strategic development of financial institutions.

Problem statement. Despite significant research on volatility measurement and forecasting, there is insufficient analysis of how volatility drives structural transformation of the financial services market, especially under conditions of geopolitical instability, technological progress, and financial digitalisation.

Unresolved aspects of the problem. The interdisciplinary connection between volatility, financial innovations (cryptocurrencies, Big Data, AI-driven analytics), and transformations of financial services remains underexplored. Knowledge gaps concern the interaction of global spillover risks, geopolitical shocks, and the adaptive capacity of financial institutions.

Purpose of the article. The study aims to identify how stock exchange volatility influences transformations in the financial services market and to propose strategies for adaptation under instability and uncertainty.

Presentation of the main material. Using an interdisciplinary approach, the article combines theoretical analysis, systemic modelling, and review of empirical studies. It shows that volatility manifests through spillover effects across interconnected markets, amplified by geopolitical risks, and intensified by digital innovations such as algorithmic trading and cryptocurrencies. The author highlights the growing role of machine learning and AI in forecasting volatility, while emphasizing the limitations of algorithmic tools and the importance of combining them with expert financial analysis. Special attention is given to regional disparities, third-party risks, and the need for hybrid analytical platforms integrating local and global expertise.

Conclusions. Volatility is both a challenge and a driver of transformation in financial services. It accelerates the introduction of new technologies, changes risk management approaches, and demands new regulatory and analytical frameworks. A hybrid model combining digital tools and human expertise can mitigate risks, improve resilience of financial institutions, and expand access to financial services in underdeveloped markets. The results provide a foundation for adaptive strategies and future research on multi-level models of volatility assessment.

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Author Biography

Serhii Zadvornykh, Private Higher Education Institution “Rauf Ablyazov East European University”

Doctor of Philosophy in Economics, Associate Professor of the Department of Finance

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