In the DeFi liquidity staking race, the ceiling of arbitrage mechanisms is determined by the interest rate spread, but survival depends on risk control. Why can some projects' arbitrage strategies operate stably? The key difference actually lies in the liquidation mechanism.

The reason stablecoins like USD1 attract crypto investors is ultimately because their underlying risk protection system is robust enough. Compared to projects that rely on a fixed liquidation rate, a smarter approach is to let the liquidation threshold move in sync with market rhythms.

**How does the liquidation threshold move? Just look at volatility**

Technically, the platform monitors the historical volatility (7-day data) and implied volatility of collateral assets like BTCB, ETH, BNB in real-time, combined with a weighted market sentiment index, to dynamically adjust the liquidation trigger line.

Take BTCB as an example. When market volatility is relatively moderate (below 20%), the liquidation threshold is set at 115%. Once volatility surges above 40%, the system automatically raises the liquidation line to 130%. What’s the benefit of this design? It prevents ordinary arbitrageurs from being instantly liquidated during extreme market conditions, providing breathing room to adjust positions.

**How to survive in extreme market conditions? Use hedging tools**

Having a dynamic threshold alone isn’t enough. The real risk control moat must be reflected in practical responses during extreme market conditions. These projects often embed hedging toolchains—by integrating with derivatives platforms, allowing users to quickly hedge positions when liquidation risk approaches, rather than passively waiting for liquidation to occur.

In other words, risk control has evolved from a passive “set the liquidation line and let it be” to an active “provide early warning + quick stop-loss channels.” For participants aiming for long-term arbitrage, this means a significant upgrade in capital safety.

**Multiple oracles + sentiment index create a more comprehensive risk model**

Many projects rely on a single data source, which is quite risky. A more robust approach is to incorporate multiple independent oracles for price feeds, combined with macro sentiment data like fear-greed indices, to build a multi-dimensional risk assessment model. When oracles conflict, the system can automatically switch to the most reliable data, greatly reducing single-point failure risks.

From parameter models → extreme market response → innovative risk control tools, the difference between good DeFi arbitrage projects and mediocre ones essentially lies in the sophistication of their risk control systems. The liquidation mechanism isn’t about being overly strict or too lenient—it’s about whether it can dynamically balance protecting funds and maintaining ecosystem stability. This is the fundamental reason why some arbitrage strategies can survive for a long time, while others frequently experience failures.