The issue of the industry window of opportunity is gradually becoming apparent. Infrastructure ultimately needs vehicles to run on it. 2022 was an early window of opportunity for infrastructure development, lasting until the activation of GPT in early 2023. Now is also a window of opportunity for the connection between AI computing power highways and vehicles. Perez's industry life cycle tells us that seamless integration is impossible.

We should review the 2021 "chicken dinner shrinking" market trend. Initially, everyone thought there would be a rapid recovery after the pandemic, anticipating a surge in overall market performance. However, as economic data was released in the second quarter, investors began to realize that there might not be a sustained overall market rally. This gradually evolved into a market focused on structural changes rather than overall market performance, leading to the "chicken dinner shrinking" trend. New energy (lithium batteries, photovoltaics, etc.) became the absolute main driver of capital inflows, with the "Ningbo Index" significantly outperforming the market and some leading stocks experiencing explosive growth. Meanwhile, traditional consumer blue chips (the Kweichow Moutai Index) and most small-cap/non-core sectors continued to suffer losses. The index remained relatively stable, but individual stocks generally declined, with trading highly concentrated in a few "group-buying" stocks. Trading became extremely congested, preventing the "group-buying" trend from spreading. When external conditions worsened, risk appetite decreased, and funds became even more concentrated in these stocks, accelerating the cycle of "the worse the market, the more funds are held, and the more funds are held, the worse the market becomes." Then, in early 2022, the collapse of these "group-buying" stocks was triggered by tightening external liquidity, a valuation correction in US stocks, underperformance of the "group-buying" stocks, falsified fundamentals, negative feedback from mutual fund redemptions, and further losses in small-cap stocks, creating a spiral cycle.

The Complete Causal Chain of the Cycle 1/ Initial Condition: Tightening of Overall Liquidity Whether the source is central bank QT, strengthened bank capital regulation, reversal of cross-border capital flows, or private sector deleveraging, the overall available "risk-bearing capacity" is declining. 2/ Trigger: Uncertainty Shock Geopolitical events, unexpected policy developments, unexpected data or earnings, or even just a single pulse of volatility can disrupt the fragile balance. 3/ First Round of Reaction: Sell-off of Risky/Marginal Assets + Deleveraging Leveraged funds, risk parity strategies, CTAs, and institutions with insufficient allocation to "marginal" assets withdraw simultaneously. Liquidity in marginal assets (overvalued growth, peripheral credit, high-yield bonds, emerging markets, some commodities, or crypto-related assets) becomes instantly scarce. 4/ Liquidity Redistribution: Systemic Liquidity Concentrates on Core Assets At this point, "certain assets" (sovereign bonds, gold, defensive/policy-supported core equities, and a few types of assets considered "safe" by market consensus) become the only acceptable collateral and allocation targets. Financing capacity tilts towards these assets. 5/ Price and Narrative Reinforcement: Core Asset Prices Rise Continuous capital inflows drive up prices, further validating the narrative that "these assets are the only truly certain ones." The certainty premium is self-confirmed by the market through price signals. 6/ Siphon Effect: Peripheral Asset Liquidity Continues to Deteriorate The rise in core assets is not neutral—it continuously draws remaining liquidity from already fragile peripheral sectors. Widening financing spreads, declining collateral values, and rising margin requirements create a vicious cycle. 7/ Accelerated Feedback: Capital Further Concentrates in the Core Institutional risk control models, passive funds, and even AI trading agents identify core assets with "better past performance, lower volatility, and better liquidity" as the optimal solution, accelerating allocation. 8/ Ultimate Consequence: Reflexivity and Vulnerability The higher the price and concentration of core assets, the deeper the system's dependence on the "certainty narrative." Once even a small crack appears in the narrative (fundamental falsification, policy shift, or external shock), the reversal will be far more severe than the initial shock. Because the margins have long been a liquidity black hole, the buffer mechanism has disappeared, and the implicit accumulation of leverage in the core will be released all at once during deleveraging.

【2026.5.15】The difference between the implied volatility of 1-month 25-delta put and call options on US tech stocks (i.e., option skewness) has decreased significantly (bottom right of the chart). While a decrease in option skewness is generally a positive sign, it is currently near historical lows, indicating excessive optimism and an underestimation of risk. Any extreme extreme in anything is a sign of a reversal, and option skewness nearing historical lows often foreshadows potential increases in short-term market volatility. Once external factors cause disruptions that fail to further drive market expectations, extreme optimism can turn into extreme disappointment. Therefore, when option skewness is at historical lows, leverage should be appropriately reduced and hedging protection increased. Similar to the VIX, extremely low volatility itself may only be noteworthy, but if several fatal combinations occur simultaneously (e.g., low volatility + high valuation + pessimistic options market + tightening PQ liquidity), especially in the RXM/SPX range... As previously discussed, this reflects the true risk appetite of market participants, meaning that option pricing is currently extremely cautious (low ratio). Meanwhile, market valuations are high, and volatility remains low (VIX remains low). Liquidity is tightening (PQ) (see the chart below for several dimensions).

【2026.5.15】 In the chart, the blue line represents the ratio of the CBOE S&P 500 Risk Reversal Index (RXM SM Index) to the S&P 500 Index, the brown line represents the Cape Ratio, and the gray line represents the VIX. The RXM SM index is an SPX long strategy packaged with options. Dividing the RXM SM index by the SP500 can serve as an indicator of options market sentiment. The ratio represents the net balance between how much the market is willing to pay for upside participation and how much it is willing to collect for downside protection. A high ratio indicates investors are more willing to sell puts to cash out, reflecting optimism and suggesting an undervalued market. Conversely, a low ratio indicates investors are unwilling to sell puts, reflecting pessimism or risk aversion, often indicating an overvalued market. If liquidity tightens or any other disturbance occurs at this time, market volatility will quickly rise. Now, following the end of 2021, Q1 has reached this level again. After a dip, the data only slightly recovered, and with the recent rise, it is approaching the historical level of the end of 2021 again. Simply put, the market is pricing in that anyone selling put options may face greater risk. If volatility is still low, this is not good news. From options data, you should "remain vigilant while sailing."

As Bitcoin (BTC) evolved from its initial definition phase to gradually face regulatory constraints and its monetary and asset attributes were clearly defined, it has become a substantial asset class that traditional financial institutions can allocate, accompanied by the continuous advancement of financial derivatives. This phenomenon includes the launch of exchange-traded funds (ETFs) and the emergence of financial derivatives such as CME futures. Traditional financial institutions can indirectly or directly allocate to BTC through various channels such as stocks, funds, and derivatives. In fact, this is similar to the development trajectory of other traditional commodities from spot to financial derivatives. In the 1980s, 1990s, and even the early 21st century, numerous similar commodity experiments occurred, with a large number of commodity exchanges and various commodities. However, only a handful survived in the first stage. In the second stage, the commodity categories we see in major asset classes today remained. Including the United States and China, some varieties survived after a final selection process. Once these assets complete their mature evolution, they gradually acquire true macroeconomic attributes or the hallmark characteristics of traditional financial assets. It has begun to be affected by factors such as global liquidity changes and portfolio management position adjustments, and its pricing logic has gradually shifted from the traditional supply and demand relationship of commodities.

The Clarity Act (to be passed by the House of Representatives in 2025, with the Senate still pushing forward) further categorizes digital assets into three types: Digital Commodities (such as Bitcoin and Ethereum), which are essentially tied to the functions of the blockchain system and are regulated by the CFTC; Investment Contract Assets (similar to securities), regulated by the SEC; and Permitted Payment Stablecoins, regulated by banks. This act will separate the previously attempted unified definition of attributes: stablecoins will primarily handle application-level payment/settlement functions (subject to strict reserve and redemption rules), while retaining the value store function as a crucial element of Bitcoin's value maintenance role, assuming the attributes of speculative assets and commodities, rather than everyday currency functions.

Commodity Exchange Traded Funds (ETFs) are essentially compliant products that package the business model of "holding commodities long-term and continuously generating rental income" and offer it to retail investors. Fund companies receive a share of the rental income earned by large investors who hold substantial amounts of commodities, lend related assets, and participate in derivatives market transactions, while also charging management fees. Fund companies are not simply optimistic about the market prospects of a particular commodity, but rather value its asset attribute of continuously generating "rent." Since May 13, 2016, the day BitMEX launched the world's first BTC perpetual contract, a funding rate mechanism has been implemented. From then on, long-term BTC holders could obtain rental income through hedging operations, marking its true transformation into a "rental asset." Before this, it existed merely as a speculative target for evangelistic beliefs; afterwards, it possessed a stable positive cash flow logic.

In the past, China's gold spot exchanges appeared to have low transaction fees, but their profits mainly relied on two sources: spreads (the difference between the buying and selling prices) and overnight fees (also known as deferred fees). Retail investors tended to use leverage and preferred to hold positions overnight. Even if the overnight fee was only 0.2% per day, it would consume most of the margin over a year, and this part of the funds ultimately flowed into the platform. For example, Shanghai Gold Exchange and large bank lending exhibited a typical "rent collection" model, with retail investors holding long positions for a long time, and deferred fees continuously flowing to large investors who held large amounts of spot gold for a long time.

Large investors hold long-term positions and collect rent through hedging transactions, effectively lowering their average cost basis. For them, Bitcoin becomes an asset that generates interest; as long as their total position size doesn't decrease, over time the cost basis becomes so low that they almost break even. Many ordinary people mistakenly view large investors simply as short sellers; they are more like landlords collecting rent. This logic was consistent with some of the previous domestic industrial commodity spot exchanges. Large investors held physical assets long-term and collected rent through warehouse receipts, financing, and delivery, continuously lowering their average cost basis. The forward spread in CME Bitcoin futures essentially reflects the market's pricing of borrowing costs during that period. Collateral fees are essentially a reflection of funding rates. Whether the forward structure is at a discount or premium, it reveals the market's expectation of holding costs, which is completely consistent with the rent-collecting logic of large physical investors.

Back in the day, Chinese gold spot exchanges enforced daily forced liquidation and settlement, with long and short positions paying deferred fees to each other. The exchanges didn't directly collect this money, but when retail investors held a large long position and leveraged highly, the deferred fees became the platform's most stable, hidden source of income—retail investors paid long-term, and the platform indirectly benefited through trading volume and liquidity. The same applies to Bitcoin spot platforms now: They primarily rely on perpetual contracts(not pure spot trading), with long and short positions settling **funding rates** every 8 hours. When long positions are in the majority, they pay short positions; retail investors holding long positions for a long time are constantly paying. The exchange itself doesn't directly collect this money, but it greatly increases trading activity and open interest, indirectly generating transaction fees, liquidity, and user stickiness, indirectly becoming a large and stable source of income for the platform. The only difference is the terminology: back then it was called "deferred fees," now it's called "funding rates," but the essence is exactly the same。

Energy price fluctuations can have a more pronounced impact on inflation expectations in situations where the job market shows resilience (e.g., low unemployment, strong job growth, and upward wage pressures). If the job market is strong and labor has strong bargaining power, it will demand higher wages to offset the rising cost of living, thus forming a "wage-price spiral." Such a spiral would make inflation expectations more persistent; Against the backdrop of a resilient job market, central banks such as the Federal Reserve tend to focus more on controlling inflation than stimulating employment. This means rising energy prices could delay a rate cut or keep rates high; Originally, the Fed's QT operation in the past six months has caused liquidity fragility, and some valued assets have already experienced considerable declines. If the Iran problem lasts longer, it will be even more detrimental to global risk assets and will further amplify the volatility of the entire market;

Liquidity tightening impacts asset markets through both the price channel (P, such as rising financing costs due to interest rate changes, as seen in the rapid interest rate hike cycle of 2022) and the quantity channel (Q, such as reducing market liquidity through quantitative tightening (QT)). Over the past six months (roughly from September 2025 to March 2026), the cumulative effect of QT has initially pressured overvalued assets, such as stocks, bonds, and certain technology or AI-related sectors, leading to amplified market volatility. If the SRF rebounds at the end of March or reserves continue to decline, signs of liquidity tightening will become more pronounced. This dynamic often precedes asset price fluctuations by approximately 90 days.