On October 11, 2025, a day destined to be written into the history of the crypto market, the industry witnessed one of the most devastating liquidations ever within just 24 hours: over $19.1 billion in leveraged positions were wiped out, more than 1.6 million traders were forcibly liquidated, and Bitcoin plunged 12% overnight.

The immediate trigger came from Donald Trump’s announcement of restarting the U.S.–China trade war and imposing 100% tariffs on Chinese goods, which became the spark that ignited the market panic. Within hours, the market trembled like an invisible earthquake — Bitcoin fell from $117,000 and kept dropping, collapsing completely after 5 a.m., losing nearly $10,000 in just 30 minutes, and touching a low of $102,000. The entire market crumbled in fear.

This was the first true full-scale flash crash since 2025, even surpassing the liquidation records of the FTX and Luna collapses. Many crypto analysts compared it to the 2021 late bull flash crash, seeing it as a potential structural turning point in the market.

Historical data shows that liquidations of this magnitude usually occur near cycle peaks.
Kyle, a researcher at DeFiance Capital, noted:

“This is almost a ‘cycle-ending event.’ The resilience of BTC and ETH indicates a clear structural divergence. Bitcoin is evolving into a sovereign-grade asset, while altcoins are once again repeating the tragedy of over-leverage.”

From a macro perspective, this crash was not caused by a single event but rather by the convergence of multiple factors:

• Excessive leverage buildup: Continuous bullish momentum drove leverage ratios to record highs, making the funding structure fragile.

• Whale precision attacks: Anonymous accounts shorted BTC/ETH with $1.1 billion on Hyperliquid, triggering a chain of liquidations.

• Policy shocks: The tariff news intensified risk aversion, prompting high-frequency institutions to auto-liquidate.

The violent market swing once again reminded everyone: crypto risk never lies on the chart — it hides behind the leverage.

In the eye of this storm, Nivex’s AI strategy system demonstrated exceptional resilience.

Powered by its proprietary AI-driven risk management model and institutional-grade strategy mirroring system, Nivex detected volatility signals in real time. Before the crash unfolded, the system automatically reduced long exposure, effectively sidestepping the core collapse phase.

According to platform statistics, institutional strategy accounts on Nivex kept average drawdowns under 1.7%, and some quantitative portfolios even achieved profits amid the downturn.

This outcome validated the robustness of Nivex’s “Intelligence + Strategy” architecture.

Nivex, in collaboration with multiple quantitative funds and strategy teams, deployed a strategy signal engine that analyzes on-chain data, market depth, position structures, and sentiment metrics to build a three-tier defense system:

• Multi-factor model alerts: Machine learning identifies abnormal volatility patterns and adjusts portfolio exposure in advance.

• Automated take-profit and stop-loss: The system executes predefined risk signals once volatility thresholds are hit, preventing emotional decisions.

• Cross-strategy coordination: The AI engine synchronizes risk exposure across strategy pools, avoiding systemic overlap.

This architecture empowers Nivex’s AI copy-trading platform with institutional-grade defense, allowing everyday users to benefit from professional-level strategies and risk management.

Nivex’s core philosophy is simple: empower retail traders with institutional-grade trading systems.

Traditional trading relies on human experience and intuition, while Nivex’s AI strategy system transforms trading into a process that is algorithmic, data-driven, and automated.

Through continuous AI modeling of market structures, Nivex generates real-time “strategy signal streams” and distributes them instantly to copy-trading users. Whether it’s long-term trend following, short-term volatility trading, or arbitrage and hedging, the AI system generates executable strategies based on historical patterns and live indicators.

This means that, even in highly volatile environments, users no longer need to react passively — the system automatically adjusts positions in response to market conditions.

Unlike human traders, AI is immune to fear and greed. It doesn’t panic-sell or overtrade. Instead, it relies on tens of thousands of historical backtests and real-time data to make millisecond-level decisions.
That’s why, during the 10·11 crash, Nivex’s AI trading engine stood out as one of the few systems that remained calm and operational at the center of the storm.

Over the past decade, the evolution of crypto trading has followed a clear path — from speculation, to strategic trading, and now to intelligent automation.

Today, AI not only understands market trends — it actively participates in decision-making and execution.
Nivex is strategically positioned at the forefront of this transformation: by integrating AI strategy systems, institutional-grade risk models, and a Web3 wallet ecosystem, it is building an intelligent trading infrastructure that bridges on-chain and off-chain, retail and institutional finance.

As market volatility normalizes and regulatory compliance advances, the next phase of exchange competition will no longer focus on “who lists more tokens,” but on who can deliver safer, smarter, and more sustainable yield systems.

The “10·11 Crash” reminded everyone once again: the market has no mercy.
In the crypto world, risk is omnipresent — but the ability to control, understand, and leverage that risk is the only path to long-term survival.

Nivex has proven through real performance:
In the most uncertain times, AI is becoming the new certainty of trading.
The future of trading belongs not only to the brave,
but to those who know how to make intelligence work for them.