Global financial markets now operate at speeds that generally tend to exceed conventional human ability. With the use of automated trading systems, cross-asset hedging models and AI-driven execution tools, most intraday movements have created a new category of systemic risk; instability produced not by leverage or illiquidity, but by velocity itself. What once unfolded over minutes now happens in milliseconds, and the gap between the pace of machine-driven markets and the pace of institutional oversight has become a structural vulnerability.

Moreover, in major equity and derivatives exchanges, algorithms now initiate the majority of orders, according to the Bank for International Settlements (BIS) and the US Securities and Exchange Commission. Thereafter, they respond to signals long before human analysts can interpret them, generating a form of price formation that is increasingly detached from deliberate judgment. 

As a result, during periods of stress, this acceleration compresses the time available for verification, leaving regulators, risk officers and central banks reacting to events that have already propagated through multiple asset classes. Contemporary crises reveal how profoundly speed reshapes market behavior. When Russian assets were frozen in 2022, the shock spread within seconds across energy derivatives, foreign-exchange exposures and clearing networks, as documented by the BIS and the European Central Bank. 

The speed trap: how algorithms trigger global market shocks

The consequent turbulence did not begin with human panic but with automated responses that triggered before any policymaker or risk committee could intervene. In the same year, the UK gilt market experienced a dramatic liquidity spiral driven by liability-driven investment strategies whose models reacted to sudden yield movements faster than the institutional mechanisms designed to stabilize them, as analyzed by the Bank of England. 

Moreover, in Asia, short-lived surges in the yen following intervention announcements were rapidly amplified by momentum-based trading bots, consistent with Foreign exchange microstructure findings from the BIS. Conversely, in emerging markets, thin liquidity magnified the impact of ultra-fast algorithmic swings, a pattern noted in International Monetary Fund (IMF)  liquidity studies. Subsequently, these episodes share a common structure where markets were not destabilized by misinformation or fundamentals, but by reaction speed, indicating a pattern that now appears across continents, linking market volatility not only to domestic policy shifts but to the increasingly synchronized behavior of automated global capital flows.

What makes this phenomenon dangerous is not speed in isolation, but the way it reorganizes market dynamics. Decisions happen faster than oversight can register anomalies. Algorithms designed by different institutions often rely on similar volatility signals, leading them to act in unison during stress. Liquidity that appears deep in calm periods evaporates instantly once risk-sensitive models withdraw from the order book, a phenomenon detailed in BIS research on flash crashes. These effects reinforce one another, producing sudden discontinuities that no longer resemble traditional market cycles.

This is no longer a regional issue but a global one. Automated contagion now moves across borders and asset classes in ways that outpace even the most sophisticated supervisory systems. An instance in this regard could be seen in the case of the Middle East. Here, automated hedging in energy derivatives has intensified volatility around geopolitical shocks, as noted in the International Energy Agency Oil Market Report. 

Furthermore, in Europe, latency races between exchanges create unstable feedback loops that spill into bond, Foreign exchange and commodity markets, a dynamic described by the European Securities and Markets Authority’s (ESMA) analysis of high-frequency trading risks. In developing economies, small signals trigger disproportionately large moves because local liquidity cannot absorb algorithmic surges. Across jurisdictions, authorities face the same asymmetry: markets respond instantly, while interventions are necessarily slower.

Regulatory lag: syncing policy with the speed of machines

Regulators, including the BIS, ESMA and the US Securities and Exchange Commission, have repeatedly warned that existing supervisory frameworks lag behind the tempo of machine-driven markets. Capital ratios, leverage rules and reporting cycles were designed for human-paced decision-making. They do not address the risks that arise when shocks propagate faster than institutional response times. If velocity has become a structural feature of modern finance, then stability will increasingly depend on whether institutions can introduce friction and transparency into systems that currently prize immediacy above all else.

However, strengthening resilience does not solely require radically slowing markets but aligning their speed with the capacity of institutions to interpret and supervise them. Several jurisdictions are exploring measures such as minimum execution times and enhanced disclosure requirements for algorithmic strategies, as outlined by the Monetary Authority of Singapore, as well as stress-testing frameworks that reflect the speed at which liquidity can disappear. 

On a different note, other proposals focus on ensuring that human judgment remains embedded in key decision pathways, so that rapid shifts in exposure cannot occur without explicit oversight. What unifies these approaches is the recognition that financial stability now hinges on reconciling machine tempo with human and institutional time.

Therefore, the deeper challenge is conceptual. For decades, stability was defined through balance sheets, leverage ratios and credit cycles. In the contemporary context, it is increasingly defined through latency. Though markets can withstand being wrong, they struggle to withstand being too fast, a conclusion echoed in BIS research on speed-induced volatility. Therefore, these institutions that remain resilient will not be those with the most sophisticated algorithms, but those capable of restoring coherence to systems that move faster than interpretation itself.

Consequently, for policymakers, the challenge is not simply technical but institutional as global markets now share a common technological substrate, while regulatory capacity remains fragmented across jurisdictions. Therefore, without coordination, speed becomes an amplifier of geopolitical asymmetries rather than a neutral feature of financial infrastructure.

In conclusion, speed has become the new systemic variable. The question facing regulators and policymakers is no longer how to manage speculation or excess risk, but how to govern markets that operate beyond human reaction time. 

In this vein, stability in the 21st century will depend on whether financial systems can reintroduce the one element they have gradually eliminated: the capacity to pause, verify and intervene before machine-speed shocks become systemic crises.

[Ainesh Dey edited this piece.]

The views expressed in this article are the author’s own and do not necessarily reflect Fair Observer’s editorial policy.