From January 29 to 30, in the UTC+8 time zone, international spot gold and silver experienced a sharp correction from historic highs, triggering a chain reaction in global safe-haven assets and derivatives markets. Accompanied by the rapid decline in gold and silver prices, contracts linked to precious metals in off-exchange segmented markets such as Hyperliquid saw concentrated liquidations within hours, with the scale of a single variety reaching tens of millions of dollars. Meanwhile, crypto-related assets and concept stocks faced simultaneous pressure, with representative targets experiencing nearly double-digit declines, indicating a clear tightening of overall market risk appetite. A cross-market volatility chain triggered by the correction of high-priced precious metals, amplified by leverage and quantification, is gradually being outlined.
Precious Metals' High-Level Retreat: Repricing of Risk Aversion
● Characteristics of High-Level Correction: In late January, international spot gold and silver showed a significant correction near historic highs, with the trend quickly switching from a previous "one-sided rise" to a rapid decline in a short time. Due to the lack of unified authoritative intraday statistics, specific points and precise declines are not cited here, but from the performance of major market transactions and volatility, it can be confirmed that this round of adjustment has exceeded the range of daily fluctuations, constituting a phase of repricing of risk aversion.
● Overlapping Macroeconomic Expectations: This round of correction is highly synchronized with changes in expectations regarding U.S. politics and monetary policy. The market is repricing around Trump's proposal to replace the Federal Reserve Chairman and push for interest rate cuts of 2-3 percentage points, with strengthened rate cut expectations implying uncertainty in the actual interest rate path and inflation direction. Some funds chose to reduce positions near the historic highs of precious metals, compounded by technical factors in derivative positions, causing macro expectations and selling pressure to coincide in timing.
● Market Interpretation Discrepancies: From public discussions, some viewpoints believe this round of decline is a "natural correction after parabolic rise," emphasizing the need for technical digestion due to the previous rapid increase; others suspect the possibility of "algorithmic trading concentrated selling," attributing extreme market conditions to programmatic sell-offs amplifying volatility. These statements are currently interpretations and speculations in the market, lacking verifiable evidence support, and should be viewed as hypotheses to be validated rather than conclusions.
Hyperliquid Liquidation Chain: Price Destruction Amplified by High Leverage
● Concentrated Liquidation Data: During the rapid decline in precious metal prices, the SILVER contract on the Hyperliquid exchange experienced approximately $70.52 million in liquidations within 4 hours, with about 99% being long positions according to a single source. This indicates that during the price reversal process, the high leverage on the long side was concentrated and exposed, triggering a chain reaction of forced liquidations, further exerting mechanical downward pressure on prices.
● Whale Liquidation Trajectory: On-chain monitoring shows that a single whale address encountered 46 consecutive liquidations during the same period, totaling approximately $29.3 million (also from a single source). This address is characterized by concentrated positions, high leverage, and insufficient buffer margin, which, once the price of the underlying asset experiences unexpected volatility, will be systematically "liquidated in batches" under the forced liquidation mechanism, amplifying transaction volumes and volatility in a short time.
● Positive Feedback of Leverage and Forced Liquidation: In such segmented derivative markets, high leverage and crowded long positions can significantly exacerbate one-sided market movements. A preliminary price decline triggers insufficient maintenance margin for some leveraged long positions, and the platform's risk control system enforces forced reductions or liquidations according to preset rules, further driving down prices and pulling more high-leverage longs into liquidation, forming a typical positive feedback loop of "price decline—liquidation—passive selling—price further decline."
● Single Source and Uncertainty: It is important to emphasize that the aforementioned $70.52 million liquidation scale, 99% long position ratio, and $29.3 million whale liquidation all come from a single data source and have not been cross-verified by multiple platforms or official audits. In extreme market conditions, anomalies in matching, price deviations, and differences in statistical criteria can distort data presentation. Readers should exercise caution when referencing these figures, viewing them as samples of risk profiles rather than a complete picture.
From Gold and Silver to the Crypto Sphere: Spillover Effects of Reduced Risk Appetite
● Concept Stock Barometer: During the same period of turbulence in precious metals, several U.S. stocks highly correlated with crypto assets faced simultaneous pressure. Public data shows that MSTR fell approximately 9.63%, while another crypto-related concept stock DFDV dropped about 11.77%, both significantly underperforming the broader market. These stocks are influenced by Bitcoin prices and sentiment, and are also sensitive to interest rate expectations and liquidity conditions, often serving as leading indicators during cross-market shifts in risk appetite.
● Transmission of Volatility in Safe-Haven Assets: Gold and silver are traditionally viewed as tools for hedging against inflation and systemic risks. When these assets experience severe volatility at historic highs, institutions with strict risk budgets often tighten overall leverage and risk exposure simultaneously. Coupled with potential interest rate cut paths and macroeconomic uncertainties, some portfolios may choose to compress positions in high-beta assets, including crypto concept stocks, thereby amplifying the selling pressure on crypto-related assets at the funding level.
● Linkage Logic Under the Inflation Hedge Narrative: Precious metals and mainstream crypto assets have long been packaged within the same narrative framework of "hedging inflation" and "hedging currency devaluation," with some funds viewing both as substitutes within the same style bucket in asset allocation models. However, in this event, there is no conclusive evidence showing that funds have migrated en masse from precious metals to crypto or vice versa. A more reasonable understanding is the "correlation of narrative and style," rather than a quantitative conclusion based on specific flow data.
● Boundaries of Data and Hypotheses: What can currently be verified is the high-level correction of precious metal prices, concentrated liquidations of Hyperliquid precious metal contracts, and the actual decline performance of crypto concept stocks like MSTR and DFDV. As for whether there has been a large-scale migration of funds across markets or whether there exists a systematic rotation path, this remains at the level of hypotheses and logical deductions. Distinguishing between objective market data and unverified or unproven hypotheses about fund migration is a key step in reducing cognitive biases during extreme volatility.
Leverage Cycles and Quantitative Trading: Technical Underpinnings of Multi-Market Resonance
● Positive Feedback of Leverage and Pegging Structures: In the precious metals and crypto markets, products that peg multiple assets or use cross-margining are increasingly common. Once high-leverage contracts are linked to spot prices, their liquidation thresholds are directly affected by spot volatility. A weakening in the spot market triggers forced liquidations of contracts, and the passive selling on the contract side further impacts the spot and related assets, forming a positive feedback loop of prices across markets and varieties, amplifying spreads and impacting already limited liquidity buffers.
● Possible Triggers of Algorithms and Quantitative Strategies: In an environment where volatility suddenly amplifies, most trend-following, volatility-targeting, CTA, and statistical arbitrage quantitative strategies may trigger stop-losses or reductions based on preset parameters. Some market participants speculate that this round of precious metal volatility contains elements of "algorithmic trading concentrated selling," but this judgment currently remains at the level of experiential deduction and observation of abnormal transactions, lacking verifiable evidence of specific strategic behaviors, and should be viewed as a technical hypothesis to be validated rather than an established fact.
● Differences in Derivative Rules and Liquidity: There are significant differences in forced liquidation rules, funding rate mechanisms, and liquidity depth between precious metals and crypto derivatives. Traditional precious metals markets are often constrained by stricter margin ratios and trading time limits, while crypto derivatives generally offer higher leverage and 24-hour continuous matching. When extreme market conditions arise, concentrated forced liquidations in the former may erupt within fixed time periods, while the latter will continuously release pressure on an all-day order book. This institutional difference shapes their respective volatility profiles across different time scales.
● Regulatory Constraints and Extreme Market Conditions: At the regulatory level, requirements for leverage limits, margin models, and algorithmic trading disclosures vary significantly between markets. Traditional precious metals markets are generally under stricter scrutiny, while some crypto derivatives platforms offer greater freedom regarding leverage limits and quantitative access thresholds. This means that when macro shocks occur, markets with looser regulations are more likely to experience the amplifying effects of high leverage combined with algorithmic trading, making the tail risks of extreme market conditions more pronounced.
New Macroeconomic and On-Chain Clues: Interest Rate Cut Expectations and Fund Layering
● Background of Interest Rate Cut Expectations: The current market is highly focused on the expectation that Trump plans to announce a new Federal Reserve Chairman and push for interest rate cuts of 2-3 percentage points, which will directly affect nominal and real interest rate paths for the coming years. If the interest rate cut process advances beyond expectations, the attractiveness of traditional fixed-income assets may decline, while the allocation weights for high-volatility and safe-haven assets will be reassessed, a process that will reshape the relative pricing benchmarks for gold, silver, and crypto assets over a longer cycle.
● Demographic Trends and Long-Term Allocation Preferences: The research brief also mentions that the U.S. may experience a decline in total population for the first time in 2026. This structural change will affect long-term economic growth expectations, tax bases, and social security burdens, thereby altering the asset allocation logic of long-term funds such as pensions and sovereign funds. In a scenario of slowing growth expectations, some institutions may rely more on assets with cash flow and dividend capabilities, adopting a more dynamic style rotation strategy for non-cash-flow-generating precious metals and crypto assets.
● Marginal Impact of New On-Chain and Exchange Products: On a micro level, events such as Bitget Wallet launching regulated USAT, Aster planning to launch airdrop of 64 million tokens on February 2, and Bybit launching ELON spot trading on February 2 add new assets and tools to the on-chain and exchange ecosystem. These new products are unlikely to change the macro volatility narrative in the short term, but at the level of segmented funds, they may have a marginal impact on fund layering and risk diversification, for example, providing some investors with new hedging and allocation vehicles to alleviate the congestion of single assets.
● Background Variables Rather Than Primary Causes: It is important to clarify that the aforementioned events such as the USAT and Aster airdrop and ELON launch are not the direct primary causes of the recent flash crash in precious metals and the severe turbulence in crypto-related assets, but rather ecological expansions and structural adjustments occurring within the same time window. From a risk perspective, they more influence the micro flow of funds and risk diversification capabilities, rather than being core variables driving cross-market price resonance.
Before the Next Round of Turbulence: Risk Checklist for Crypto Traders
● Common Cracks in Leverage and Liquidity: The recent flash crash in precious metals and concentrated liquidations of Hyperliquid precious metal contracts, combined with significant corrections in crypto concept stocks like MSTR and DFDV, expose similar vulnerabilities in a cross-market environment: high leverage, crowded long positions, and limited liquidity. Once macro expectations reverse or prices retreat from historic highs, forced liquidation mechanisms and passive selling will quickly amplify volatility, bringing synchronized pressure to all leveraged structures.
● Key Signals for Traders to Monitor: For crypto traders, in an environment of increasing cross-market volatility, it is essential to incorporate macro interest rate expectations, policy personnel changes, and fluctuations in safe-haven asset prices into daily monitoring, rather than solely focusing on on-chain data and coin prices. Additionally, in managing derivative positions, attention should be paid to the cumulative effects of single and cross-asset leverage, reserving sufficient margin buffers to avoid being caught in forced liquidation chains when prices initially reverse.
● Risk Control of Data and Opinions: In extreme market conditions, social media and single data sources often amplify emotions and biases. The liquidation scales, clearing details, and judgments regarding "algorithmic concentrated selling" involved in this event are mostly based on limited sources and unverified clues. For crypto traders, constructing a multi-dimensional risk monitoring framework—including macro data, market depth, on-chain funds, and cross-market correlations—and maintaining caution towards all unverified opinions is the only realistic path to gaining an advantage before the next round of turbulence arrives.
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