Author: Newfire Technology
Mr. Fu Peng, Chief Economist of Newfire Group, was invited to participate in Wiki Finance EXPO Hong Kong 2026 and delivered a keynote speech. Starting from the global liquidity framework, Mr. Fu Peng shared his core views on the current global macro assets and market trends, and made a systematic judgment on the underlying logic of the crypto market.
Mr. Fu Peng, Chief Economist of Newfire Group, delivering a speech at Wiki Finance EXPO Hong Kong 2026The following is the full text of the speech:
Today I will share with you my views on major global markets from several dimensions. First, let's talk about liquidity. Regardless of the type of asset, including mainstream crypto assets, they are all fundamentally linked to global core liquidity.
After the 2008 financial crisis, global liquidity reached a cyclical peak from 2008 to 2021. Liquidity cannot be understood simply by looking at interest rate hikes or cuts in the news; it has three dimensions that you must remember.
Interest rate hikes and cuts are only changes in the yield curve and do not represent the complete liquidity environment. Observing liquidity can be broken down into three things: the amount of water in the pool, the temperature of the water, and the distribution of capital pressure within the pool. The underlying logic can be simply understood as P/Q×G. From a professional perspective, liquidity can be tracked through interest rates, the yield curve, the Federal Reserve's balance sheet, open market operations, etc. But there is also a simpler observation method: in current traditional trading, mainstream crypto assets like Bitcoin are widely regarded as leading indicators of liquidity strength.
01. From "Frenzied Speculation on Junk Assets" to "Shrinking Circle": Two Faces of the Liquidity Cycle
After the 2020 pandemic, the world experienced an extreme easing window of low interest rates and central bank balance sheet expansion. During the easing cycle, global financial assets exhibited a typical characteristic: frenzied speculation on junk assets.
For example, the short squeeze of GameStop in the US stock market and the surge of numerous shitcoins in the crypto market were essentially the result of liquidity flooding—when there is too much money, any asset can be pumped. However, when liquidity begins to contract overall, the market experiences a "shrinking circle" phenomenon: capital actively distinguishes between good and bad assets, and inferior assets are abandoned. This process of squeezing out bubbles started in the second half of 2021.
From the second half of 2021 to 2022, typical cases include Bitcoin in the crypto market falling from over $70,000 to around $20,000, and Nvidia in the US stock market dropping about 64-65% in 2022. This process is like squeezing water from a sponge, continuously squeezing out market bubbles.
This year, the real turning point occurred in November last year. 2021 was the peak of central bank balance sheet expansion, while the end of last year was a critical juncture of dual tightening with liquidity and balance sheet reduction. Simply put: draining the pool does not mean funds tighten immediately when balance sheet reduction starts; only when reduction progresses to a certain point does the market truly feel capital pressure.
In November and December last year, when Bitcoin was around $110,000, I had a bet with Li Lin: that crypto assets would likely halve in the coming year. If that happens, it would confirm again that the underlying logic of crypto assets is entirely tied to global liquidity.
Key observation indicator in November last year: the Fed's SRF open market operations. This indicator shows that after balance sheet reduction reached a critical point, the market had already experienced structural capital pressure. You need to understand that when banks tighten credit and liquidity contracts, not everyone is short of money; capital pressure is transmitted in layers: highly leveraged and weak entities are the first to run out of funds, while high-quality leading entities still have ample funds. As liquidity pressure transmits layer by layer, the capital market experiences a "shrinking circle": capital first sells off peripheral, liquidity-sensitive weak assets, and continuously concentrates on the most core, highest-certainty assets.
Many retail investors in crypto trading have a misconception: when the crypto market is sluggish, they move all their funds to trade US stocks. This is a very retail-oriented mindset. Objectively, during a liquidity tightening cycle, funds will first clear out all high-beta, high-speculation assets from portfolios, with cryptocurrencies and small-cap thematic stocks being prioritized for reduction. When money is abundant and liquidity is loose, funds are willing to speculate on various junk assets; when money is scarce and liquidity tightens, funds will only focus on core assets with real value. This is the essence of the "shrinking circle" market.
02. Key inflection point in the AI industry: free cash flow returns to zero, capital expenditure narrative completely invalidated
Since November last year, global funds have been continuously converging on the main line of long-term productivity upgrades, namely the AI track. The logic of the AI track can be compared to large-scale fixed asset investment, and it is easier to understand by citing the example of domestic infrastructure.
In 2001, the core market issue was large-scale domestic infrastructure construction. As the old saying goes, "If you want to get rich, build roads first." At that time, Lin Yifu and Xie Guozhong were both discussing the driving effect of highway and railway infrastructure on the economy. In 2002, the Two Sessions finalized the infrastructure development direction. In 2003, central fiscal and land fiscal supporting funds were fully implemented, and national road and bridge projects started in batches, entering a long-term capital expenditure cycle. In 2004, the core targets for institutional allocation were infrastructure upstream equipment and raw material companies such as Sany Heavy Industry and Conch Cement.
The analogous logic is fully applicable to the current AI track, and the underlying laws of the industry will not change just because it is labeled "AI." In the first half of AI, applications like ChatGPT spurred corporate willingness to invest in capital expenditures. Starting in 2023, global tech companies concentrated on building digital infrastructure, namely computing power and data centers. Large-scale digital infrastructure construction will drive upstream hardware, storage, optical modules, HBM, and other industry chain targets to benefit. Samsung Electronics, SK Hynix, and TSMC correspond to the steel, cement, and construction machinery of the infrastructure era. However, the second quarter of this year is a key inflection point for the entire industry chain, compounded by the dual variable of liquidity contraction.
After Google's earnings report yesterday, mature investors could clearly detect that the main market logic of the past two to three years has become invalid. In 2023, 2024, and 2025, the market rule was simple: if internet giants increased AI infrastructure and expanded capital expenditures, the market would give them high valuations. But after the earnings reports of major companies in the second quarter of this year, even with capital expenditures maintaining high growth, stock prices fell instead.
The core reason is that investors have captured a key data point: all leading companies heavily investing in AI infrastructure have seen their free cash flow drop to zero. The most critical indicator in Google's earnings report last night was free cash flow. Many investors still cling to the old logic, believing that as long as capital expenditures continue to expand, stock prices will rise. That era is over.
The market pricing logic has completely shifted: previously, it was about the scale of capital investment, but now funds will question whether infrastructure investment can generate sustained traffic and revenue to achieve cost recovery. Free cash flow returning to zero is a landmark signal of the AI industry transitioning from the first phase to the second. If companies plan to continue increasing capital expenditures, they can only do so through external financing such as issuing stocks or bonds. External funds come with costs, and investors' scrutiny standards will become extremely stringent.
Let me give you a refined tracking indicator: the ratio of capital expenditure (CapEx) to cloud business revenue growth. Currently, Google's ratio is about 1.9, meaning that for every 1.9 yuan invested in infrastructure, only 1 yuan of cloud business revenue is generated. This is the core reason why the capital market is unwilling to continue giving high valuations.
The overall funding environment is tightening, global funds are continuously converging on a few high-certainty assets, and coupled with the industry cycle shift, the "shrinking circle" market will inevitably experience severe risk fluctuations.
Let me use NVIDIA as an example to fully outline the industry cycle: 2022 was the starting point for confirming NVIDIA's industry cycle, when its market cap fell from trillions to hundreds of billions; after the explosive launch of ChatGPT, NVIDIA officially entered the value growth phase. In 2023 and 2024, NVIDIA's logic was fully closed: continuous earnings growth, global AI capital expenditure driving order expansion, market cap successively breaking through 1 trillion, 2 trillion, and 3 trillion, with extremely low stock price volatility and almost no deep correction risk.
But after returning from a research trip to Singapore in June 2024, I warned major financial institutions of risks: NVIDIA's business operations, industry supply and demand, and industry fundamentals were all fine; the risks all came from off-market financial leverage.
Now, the new generation of post-2000 investors has a serious cognitive misconception, believing that stock price trends must perfectly match fundamentals. This view is completely wrong! Capital market pricing trades on market expectations, which can significantly lead the true fundamentals of a company.
Here's an example: the current industry situation is that HBM capacity is tight and supply is insufficient. The fundamental fact is correct, but it cannot be deduced that stock prices will continue to rise. This is a typical cognitive bias: earnings reports and capacity reflect the current reality, while stock prices trade on future expectations. Fundamental data will lag significantly behind market pricing. This is my practical experience from over two decades in the industry.
In July 2024, NVIDIA plummeted 20% in just a few trading days, and on the same day, the Japanese stock market fell 10% in a single day. At that time, many researchers issued reports attributing the decline to the Bank of Japan's interest rate hike and the unwinding of yen carry trades. This was just a superficial explanation. The underlying truth is: global funds poured into a few high-certainty assets, and extreme certainty breeds extreme greed, directly manifested in investors疯狂加杠杆.
Let me give a simple trading analogy: two of us are playing cards, your card is 6, mine is 5, and you clearly know your hand is superior. Ordinary retail investors would go all in, but a qualified trader would use full leverage to bet everything. The core conclusion must be remembered: certainty breeds greed, and everything has two sides; the operation corresponding to greed is adding leverage. The market unanimously expects Nvidia to have sufficient long-term orders, and traders will continuously add leverage to amplify returns—this is a trader's instinct. Once leverage accumulates to a critical point, it will inevitably trigger violent fluctuations and rapid declines.
The current market is replicating similar scenarios: some memory chip stocks have no industry headwinds, stable business operations, full orders, and steady earnings growth, yet their stock prices frequently plunge sharply. Many young traders in the Korean market made substantial profits one day and suffered huge losses the next. The root of the problem is not Samsung or SK Hynix, nor the HBM supply-demand chain, but the excessive accumulation of leverage in the market.
The underlying logic is exactly the same as Nvidia's flash crash in July 2024: high-certainty assets breed leverage bubbles, and when leverage hits a critical point, a crash is inevitable—there is no such thing as a permanently sustainable leveraged rally. Here's a simple risk judgment criterion: when young graduates with no practical experience pour all their funds into leveraged bets on Samsung and SK Hynix, it means risk is approaching. When a niche professional track is flooded with speculative retail investors, a bubble burst is only a matter of time. In recent years, the market has been in a capital contraction cycle. Everyone knows a few core high-certainty assets, but the risk lies not in industry fundamentals but in liquidity and leverage—this must be watched carefully.
The current market has reached a critical inflection point in the first phase of AI. The narrative of pure capital expenditure expansion has run its course, and the market will experience significant volatility and valuation corrections. For the overall U.S. stock market this year, maintaining a sideways consolidation is already an optimistic expectation. Some may argue that after the March sell-off, the market rebounded in May and June. But it's important to distinguish that the May-June rally was an extreme structural rally, with only a handful of stocks lifting the indices while the vast majority continued to decline. The A-share market structure over the past year has been exactly the same: 55% of stocks are priced below their levels at 3000 points, with only a few AI leaders supporting the indices.
To summarize the current market environment: tightening liquidity, extreme market divergence, and a key turning point in the AI industry cycle. Again, the long-term development logic of AI has not changed, and productivity upgrades are a clear main line, but you cannot blindly hold assets long-term; you must use a complete industry cycle approach to stage your positions.
I have built a five-layer complete analysis framework: industry layer, economic layer, inflation layer, liquidity layer, and market layer. Currently, there is no need to invest significant effort in dissecting the economic layer; the industry, liquidity, and market layers are the core of analysis, and the weight of macroeconomic analysis is greatly reduced. Some may ask whether it is still necessary to deeply analyze the U.S. economy. The answer is absolutely not. The reason: U.S. companies are continuously expanding capital expenditures on a large scale, and the household sector completed deleveraging as early as 2008. In other words, you don't need to scrutinize high-frequency economic data; the core characteristic of the U.S. economy is just one word: resilience.
03. Global Market Landscape: The Only Main Line is AI
At the market level, the only main line globally is artificial intelligence. Currently, global capital has only this core investment logic. Looking at globally allocable assets, the core markets in the future are only Japan, South Korea, Taiwan (China), Mainland China, and the United States. Other regions have very low allocation value; in Europe, only ASML is worth attention, and other assets have no allocation significance.
Everyone can think about two questions: Is the current trend of the Korean stock market related to South Korea's domestic economy? Not at all. Look at the Japanese stock market—is it linked to Japan's domestic economy? Also not. Looking closely at the core assets of the Japanese stock market, they are all upstream equipment manufacturers in the AI supply chain. Most market attention is focused on Samsung and SK Hynix, but the core production equipment purchased by both companies comes from Japanese firms, and the entire supply chain is fully connected. The only core asset in Taiwan (China) is TSMC; there are no other core industry companies with allocation value.
The entire AI track is essentially a productivity-driven industrial investment with fixed cyclical patterns. Let me explain the core conclusion: the point in Q2 when the free cash flow of major tech giants drops to zero is the major turning point for the market. Around this inflection point, the entire asset pricing logic of the market will completely reverse—this must be kept in mind.
The AI supply chain is divided into upstream, midstream, and downstream, each with its own independent industry life cycle, with clear sector rotation and allocation windows. Do not treat AI as a faith and blindly hold long-term; simply speculating on AI concepts will definitely lead to pitfalls. Many people ask if I am bearish on AI. This question itself has a logical flaw. Over the past decade, the market has reached a consensus: artificial intelligence is the core main line for the next generation of productivity—there is no dispute about this. Being bullish on a track does not mean blindly holding a single asset at any time. Nvidia, as a core upstream hardware stock, has completed its high-growth cycle and entered a mature blue-chip phase from 2025, which is why its gains have narrowed significantly from last year to this year. It won't be long before Samsung and SK Hynix also enter a mature cycle, and the overall growth rate of the upstream hardware sector will slow, with growth gradually shifting to downstream links.
The complete AI industry cycle rhythm forecast: 2022 was dominated by upstream hardware, 2026 will see software layer valuation digestion and reshaping, and around 2030, the terminal application layer will undergo valuation adjustments and repricing. The complete AI industry mega-cycle lasts about 20 to 25 years, and we have already gone through 10 years. The first decade's main line was upstream hardware infrastructure, and the next decade's main line will be terminal applications.
However, there is currently a cycle gap. The next 10 to 18 months represent an industry transition window. During this window, do not go all in; strictly follow the industry cycle rules to stage your positions and avoid large volatility risks. Here, distinguish a key concept: AI code tools and development aids from a programmer's perspective belong to the industry supporting tool layer, not the terminal application layer, and their valuation logic differs greatly.
04. Karen Walsh and the Liquidity Paradigm Shift: Central Banks No Longer Backstop, Crypto Assets Enter Maturity
Finally, I will return to the liquidity dimension to explain, which is also a core variable highly relevant to crypto assets. Why is the new Fed Chair Karen Walsh a key signal? Her appointment declares a complete rewrite of the central bank's core policy framework built by Bernanke after the 2008 financial crisis.
I wrote an analysis note in January: This personnel adjustment means the central bank's policy returns to the old path before 2008. Briefly review the policy background: The 2008 financial crisis exposed huge systemic financial risks. Policymakers learned from the Great Depression of 1929: completely laissez-faire markets cannot stabilize on their own when a crisis hits. Therefore, after 2008, Keynesian stimulus policies were implemented on a large scale globally.
Bernanke and Yellen, successive Fed chairs, all followed the same core idea: after a financial crisis, the central bank must step in to support and rescue the market. But any policy has two sides, consistent with the leverage logic in investing. Leverage can quickly amplify gains, but it can also directly lead to account liquidation. Central bank rescues can quickly calm market panic and avoid a repeat of the Great Depression, but long-term unlimited backstopping by the central bank breeds market speculation and creates large-scale asset bubbles.
There is a professional term in the market called "Fed put": as long as the market falls, funds dare to buy blindly, with all traders betting that the central bank will definitely step in to rescue. When the market forms a unified expectation that investment profits go to investors and loss risks are borne by the central bank, all financial assets become severely overvalued.
The core theme of all Karen Walsh's public speeches can be summarized in one sentence: The central bank only fulfills its statutory duties. The two core statutory goals of the central bank are stabilizing employment and controlling inflation, and it will not routinely backstop the stock market. With continuous technological progress and steady improvement in productivity, the central bank has the conditions to exit the long-term backstop model.
It can be compared to family education: when a child enters high school and has independent living ability, parents cannot handle everything and foster dependence. After Karen took office, many market participants one-sidedly interpreted it as expectations of rate cuts and balance sheet reduction, but the core focus is actually balance sheet reduction, which is less related to short-term interest rate changes. The core issue is how to orderly complete balance sheet reduction and return the central bank's function to the standard positioning before 2008.
This represents the complete end of the largest global liquidity easing cycle in human history from 2008 to Karen's appointment. Therefore, do not harbor illusions: in the next 5 to 10 years, there will be no repeat of the comprehensive flooding and across-the-board asset appreciation from 2008 to 2026. Funds will flow back to core assets with genuine long-term value. This is a key turning point in liquidity that will completely rewrite everyone's investment strategy. Investment logic will shift from comprehensive diversification and simultaneous appreciation of all asset classes to focusing on a few high-quality core targets.
The crypto market will also undergo similar changes. Many traders have observed: Bitcoin and Ethereum market caps are gradually stabilizing, volatility continues to decline, market liquidity is becoming stable, and market participants are becoming institutionalized. These characteristics are typical of core assets that survive after bubble cleansing. The narrative logic of speculating on air coins in the past has completely failed.
Liquidity is the top core influencing factor for all financial assets. Everyone must thoroughly understand this analytical logic this year. By following the liquidity framework to deconstruct industries and corporate fundamentals, the thinking for analyzing various assets will become much clearer. Today's sharing time is limited, so I cannot break down the five-layer analysis framework in detail one by one.
I prefer to discuss the underlying logic and analytical methodology with everyone. Once the underlying thinking is straightened out, looking at short-term micro fluctuations in the market will not cause excessive entanglement. My sharing ends here. I hope it can bring inspiration to everyone. Thank you all.
