Guest editorial: Navigating systemic financial risks in a globalized and digitalized economy

In the third decade of the twenty-first century, the global financial system stands at an unprecedented structural crossroads. Many countries have made significant progress in advancing global economic integration and digitalizing their financial systems to enhance market efficiency and connectivity. While this dual evolution has optimized financial resource allocation, it has also profoundly reshaped the generation mechanisms, transmission pathways and governance boundaries of systemic financial risk. As highlighted in the IMF's October 2025 Global Financial Stability Report ^[1], the global economy is operating on “shifting ground beneath the calm”, where surface-level resilience masks deep-seated structural vulnerabilities.

In this context, researchers have begun to explore the evolution of systemic financial risk within a globalized and digitalized economy. Acemoglu et al. (2015) show that financial networks exhibit a distinct phase transition, where dense connectivity buffers minor shocks but facilitates systemic risks once a critical threshold is surpassed. Shifting to digital disruption, Jia (2024) finds that FinTech penetration is positively associated with increased bank risk-taking, a process primarily driven by the erosion of bank charter value. Furthermore, Elekdag et al. (2025) find that higher FinTech penetration generally heightens risk-taking by financial intermediaries. However, they provide evidence that stronger domestic institutions can reverse this effect, leading to reduced risk-taking. Moreover, researchers have explored the implications of extensive global interconnections, particularly the propagation of shocks through international production and geopolitical networks. Di Giovanni and Hale (2022) demonstrate that global production linkages play a quantitatively important role in risk propagation, accounting for nearly 70% of the total impact of US monetary policy shocks on global stock returns. Caldara and Iacoviello (2022) develop a news-based Geopolitical Risk (GPR) index to show that both geopolitical threats and actual events significantly increase disaster probability and amplify downside risks.

Overall, both globalization and digitalization play a crucial role in reshaping the modern landscape of systemic financial risk. While these forces enhance financial integration and service efficiency, they also create complex network effects and digital competition that can amplify financial vulnerabilities. Through mechanisms such as global production linkages and FinTech-driven market shifts, the stability of financial systems is increasingly susceptible to cross-border shocks and structural disruptions. Further analysis of the evolving nature of systemic risk in this interconnected environment is crucial for enhancing the resilience and governance of the global financial system. To this end, we have organized a special issue titled “Navigating Systemic Financial Risks in a Globalized and Digitalized Economy” to explore these critical dynamics and broader research topics in this area.

We received numerous submissions in response to our call for papers, showing a growing interest in managing systemic financial risks in a globalized and digitalized economy. After a rigorous peer-review process, twelve papers were selected for this special issue. The authors are from China, the United Kingdom, Spain and Tunisia. These papers deepen our understanding of systemic risks in the modern financial landscape and offer valuable insights in the following key areas.

The first group of papers examines financial network resilience and systemic stability. Focusing on the structural architecture of financial systems, Ouyang et al. (2025) utilize the RHOSTS approach and a coupled-map-lattice model to investigate higher-order dependencies in Chinese sectoral risk connectedness networks. They find that the sectoral network exhibits pronounced higher-order interactions, with four-sector synchronous resonance as the prevailing motif. Moreover, while system-wide resilience increases over time, marked heterogeneity across sectors persists.

From the perspective of firms' systemic risk and non-financial stabilizers, Cao et al. (2025) examine how corporate social responsibility (CSR) influences firms' systemic risk. They measure firm-level risk using the TENET method and analyze the underlying mechanisms. Their results show that CSR acts as an internal stabilizer, significantly reducing a firm's systemic risk by improving its financial performance and attracting stronger external supervision. This mitigating effect is particularly strong during higher economic policy uncertainty periods, among firms with intense industry competition and in non-state-owned enterprises. Furthermore, the study reveals that CSR can reduce both the reception and emission of systemic risk, with a more pronounced mitigating effect on reception.

Furthermore, focusing on the impact of policy shocks on the banking sector, Fang and Peng (2025) investigate how China's 2009 banking deregulation influences bank risk-taking. Using a difference-in-differences (DID) approach and a three-stage regression strategy, they find that deregulated banks exhibit significantly higher levels of risk-taking. The authors identify a “balance sheet capacity” channel as the key mechanism: deregulation helps strengthen banks' net interest margins, which enhances their balance sheet capacity and subsequently increases their risk appetite. Beyond the impact on stability, the study shows that deregulation also benefits the real economy by improving long-term credit access for smaller firms in regions with limited credit availability. Ultimately, their findings highlight a critical trade-off for policymakers between supporting economic outreach and maintaining financial stability in a deregulated environment.

As digitalization reshapes the financial landscape, several papers analyze how new technologies and digital assets influence systemic financial risk. Starting with the role of digital inclusive finance in risk governance, Sun et al. (2025) investigate how digital inclusive finance affects systemic financial risk. They develop a spatial game model and test their hypotheses using city-level panel data from China. Their findings show that digital inclusive finance reduces systemic risk by enhancing resource allocation efficiency, an effect that is especially strong under strict financial regulation and in China's central and western regions. Furthermore, the study reveals that the breadth of digital coverage provides a stronger mitigation effect than the depth of its usage, suggesting that expanding financial service access is key to maintaining stability in underdeveloped areas.

Focusing specifically on the banking sector, Huang et al. (2025) use a fixed-effects model and quarterly data from 36 listed Chinese commercial banks to examine the impact of digital transformation. They find that a moderate level of digital transformation reduces banks' systemic risk by lowering both bank-specific tail risk and systemic linkage to extreme market shocks. However, their results reveal an asymmetric relationship, suggesting that while moderate digitalization is beneficial, excessive transformation could actually increase risk. The study also shows that national commercial banks experience a more significant risk reduction from digitalization compared to regional banks, providing guidance for the appropriate pace of technological change.

Regarding the volatility and management of digital assets, Zhou and Guo (2025) analyze high-frequency data from nine major cryptocurrencies to develop a multidimensional risk extraction framework. They employ a threshold optimal detection model to separate jump from continuous behaviors and apply filtering techniques to decompose continuous risk into trend and cyclical components. This approach, supplemented by wavelet coherence analysis, allows for a precise examination of market fluctuations across different time scales and reveals the various risk features within the cryptocurrency market. Finally, the study proposes differentiated hedging strategies, providing actionable solutions for investors to manage sudden jump risks through the use of derivatives like options.

Furthermore, the influence of public perception on digital market stability is analyzed by Ghosh et al. (2026). Using machine learning models and Reddit sentiment analysis, they investigate how public perceptions of global political leaders affect the cryptocurrency market. They find that social media sentiment regarding leaders such as Donald Trump, Vladimir Putin and Narendra Modi significantly influences the crypto market outlook. Their study suggests that tracking social media indicators can help investors better anticipate speculative behaviors in the cryptocurrency market.

As a shared global challenge that transcends national borders, climate risk has emerged as a critical source of systemic concern, as explored in the following papers. Regarding the systemic impact of climate policies, Jiang et al. (2025) examine how climate policy uncertainty (CPU) affects intersectoral risk contributions in China. They employ a TVM-MIDAS Copula model to capture dynamic tail dependence with tail memory advantages. The results indicate that the real estate sector has the greatest tail dependence on the market, and the raw materials sector has the longest memory of upper tail dependence. Furthermore, the authors find that CPU has a mixed impact on different sectors during moderate market declines but amplifies the volatility of systemic risk contributions across all sectors when the market plummets.

On the other hand, Xing et al. (2026) explore the economic consequences of climate risk by applying critical transition theory. Using VAR models and Granger causality tests, they capture dynamic shifts in the climate system and examine their impact on key economic sectors, including agriculture, industry and services. Their empirical evidence shows that climate risk raises agricultural production costs and reduces industrial growth in the short term, while increasing service sector output. Although these negative effects are reversible in the long term, the findings underscore the need for targeted policy recommendations to enhance climate resilience across different parts of the economy.

Focusing on the volatility of carbon markets, Wang et al. (2025) investigate the drivers of China's Emission Trading System (ETS) by analyzing mixed-frequency data from the Hubei, Guangdong and Shenzhen markets. They integrate exogenous factors in the aspects of economic, financial, energy and environment, to identify key drivers of ETS market volatility. Their findings show that carbon price volatility is primarily driven by the energy sector, with limited influence from policy and environmental factors. The study demonstrates that the Adaptive-Lasso method significantly enhances forecasting accuracy, offering valuable insights for developing countries seeking to establish stable carbon pricing mechanisms.

The final group of papers addresses how globalized markets react to geopolitical turbulence. Focusing on sudden geopolitical turbulence, Khemakhem and Gallas (2025) utilize a TVP-VAR framework and frequency-domain analysis to study the impact of the Israeli–Hamas conflict on global market volatility. Their research shows that the conflict significantly increased risk spillovers, tail risk transmission and the overall interconnectedness between global commodities and financial markets. Moreover, energy and agricultural assets are identified as the primary sources of volatility, while major indices such as the US dollar and MSCI World play key roles in spreading shocks across sectors. Their study emphasizes the high sensitivity of globalized markets to geopolitical instability and identifies gold and Bitcoin as effective hedging tools during such crises.

Expanding the focus to a global scale, Azam et al. (2025) conduct a cross-country analysis of 54 countries to examine how geopolitical risks influence green finance instruments such as green bonds and green credit. They find that geopolitical uncertainty generally hinders the development of green finance. However, the study reveals that institutional quality plays a crucial moderating role; high institutional quality can buffer against adverse geopolitical effects and even turn negative impacts into positive outcomes. This highlights the importance of strengthening regulatory frameworks and the rule of law to safeguard sustainable investment flows in a volatile globalized environment.

In advancing research on managing systemic financial risks, the categories and findings outlined in the twelve papers of this special issue provide a valuable starting point. However, these contributions cannot fully encompass the rapidly shifting landscape of financial stability and the emerging systemic risks in an era of deep globalization and digital disruption. We believe that researchers can further explore the complexities of systemic financial risk from several additional perspectives.

First, technological frontiers and algorithmic systemic financial risks. (1) The impact of artificial intelligence and machine learning on systemic financial risks. This includes investigating how autonomous trading algorithms and large language models might create new forms of financial herding behavior or flash crashes in digital asset markets. (2) Systemic financial risks inherent in decentralized finance (DeFi) and central bank digital currencies. Research is needed to model the liquidity and smart-contract vulnerabilities within DeFi protocols and their potential to transmit financial shocks to the traditional banking system. (3) Cyber-resilience and systemic financial infrastructure security. Assessing how large-scale cyber-attacks on systemic financial payment systems or cloud service providers could trigger widespread financial contagion across globalized markets.

Second, globalization and complex network spillovers. (1) Real-time monitoring of geopolitical risk transmission. Developing dynamic indicators to quantify how sudden geopolitical shifts reshape global capital flows and commodity-financial linkages. (2) Systemic implications of global supply chain restructuring. Analyzing how the transition from “offshoring” to “friend-shoring” affects the financing demands and risk profiles of multinational enterprises and their lending banks. (3) Cross-border spillovers of digital financial regulation. Investigating how divergent regulatory standards for digital assets across different jurisdictions might create opportunities for regulatory arbitrage and systemic vulnerabilities.

Third, adaptive governance and policy innovation. (1) Regulatory technology and supervisory technology applications. Evaluating how high-frequency data and blockchain-based auditing can enhance the ability of regulators to identify “early warning” signals of systemic stress in real-time. (2) Coordinating climate-related macroprudential policy with financial innovation. Exploring how digital inclusive finance and green fintech can be harmonized with traditional stability tools to manage the dual challenges of CPU and digital transition. (3) International cooperation in managing digital-financial risks. Designing frameworks for cross-border resolution mechanisms specifically tailored for systemic fintech platforms or global stablecoin issuers.

We believe that greater engagement from scholars in these issues will significantly enhance the understanding of the relationship between globalization, digitalization and systemic financial risk. Such research will be essential for promoting the resilience and governance of the global financial system in an increasingly interconnected world.