Author: Wang Chuan. This article is a sequel to “Wang Chuan: After Old Wang Next Door Invested in Storage Stocks and Made Thirty Times His Money, How Can He Not Be Anxious (Part 6) – The Trap of Homogenized Commodities.”
There is a term in the software services industry called Net Dollar Retention rate (NDR), which measures how much a customer continues to pay after initially paying one dollar. If NDR is over 100%, revenue is increasing; if it’s below 100%, it’s decreasing. However, when this term becomes “annualized” Net Dollar Retention rate, some people start to play dirty. For example, if a certain AI company’s revenue grows by 50% within three months, executives might boast of a Net Dollar Retention rate of 500% (i.e., 150% to the fourth power). Anyone who has done business knows that high growth cannot be sustained long-term, and sudden stagnation or reversal is common, yet companies often pursue financing regardless of the consequences.
During the rise of an industry bubble, a significant portion of demand is not long-term rigid but rather exploratory, driven by panic and liquidity. This demand has “reflexivity”: if others are exploring, panicking, and liquidity is pouring in madly, I will also rush to join. Once someone goes bankrupt, the situation reverses, liquidity tightens, and these exploratory demands quickly vanish.
At the stock market level, there are also speculative buyers driven by “reflexivity.” During the uptrend, they follow suit and increase leverage, pushing stock prices to extremes; once the situation reverses, they quickly scatter. Transaction prices are ultimately determined by marginal buyers and sellers, and the high prices of bull markets and low prices of bear markets are precisely created by these speculators.
We have “reflexivity” structures existing simultaneously at the physical and financial levels. During the industry’s uptrend, product demand creates a tsunami-like positive feedback loop, attracting speculators, which in turn creates a huge positive feedback loop at the financial level, further driving up asset prices. These positive feedback loops at both levels only stop and reverse when they simultaneously encounter rigid constraints. Once reversed, they form downward positive feedback loops that escalate like avalanches and mudslides.
The storage industry, semiconductor industry, and the entire data center industry chain face an even greater risk: unlike the precise four-year halving cycle defined in Bitcoin’s code, there are no statutory rules guaranteeing that stock prices will rebound within four years after a fall. In fact, Micron did not surpass its 2000 stock price high until 2024, and Intel and Cisco until 2026, experiencing painful drawdowns of over 80% or even 95% in that quarter-century. For the high-tech and hardware industries, the optimistic spirit of Ah Q’s “eighteen years later, I’ll still be a good fellow” is not applicable.
One reason for this phenomenon is the “bullwhip effect” in the hardware industry supply chain. When the industry completely reverses, the disappearance of demand is instantaneous, but supply output has delays and rigidity. Overcapacity will continue to worsen, and it will take several years to digest and reach equilibrium. Even when equilibrium is reached, the severe supply-demand imbalance from the previous uptrend will never return.
Another more subtle reason comes from the narrative migration brought about by the downward bullwhip effect. The construction of narratives is essentially a recruitment mechanism aimed at finding a greater fool. When liquidity is high, many overvalued narratives that cannot withstand scrutiny find buyers. The frenzied high valuations during the uptrend are the result of accelerated exponential growth driven by multiple “reflexivity” factors, attracting hot money to support dream valuations. Once growth slows, hot money immediately leaves to chase the next good story.
Taking the profits and stock price comparison of three major companies over twenty years as an example: Intel’s profit in 2020 was double that of 2000, but its highest stock price was lower; Micron’s profit in 2020 increased by nearly 80%, but its stock price was 20% lower; Cisco’s profit in 2020 was more than four times that of 2000, yet its stock price was only about 60% of that in 2000. Twenty years later, although the corporate shells are stronger, the soul of the ultra-high valuation narrative has long departed.
After repeatedly succeeding during the rise of an investment bubble, an individual forms two cognitive imprints: first, they equate current strong demand with sustained strong demand, believing that short-term high growth will continue uninterrupted. They ignore negative information, view declines as buying opportunities, and believe that rising prices are the ultimate truth.
Second, they believe that making quick and large profits is easy, i.e., doubling returns within a year. Fund managers who pursue stable returns are seen as old-fashioned. Warren Buffett once said, “The line between investing and speculating has never been clear, but if most participants are successful repeatedly, the line becomes blurred. Making money effortlessly is the fastest way to lose your mind.”
At this stage, it is a situation with asymmetric returns and risks. Continuing to play might yield higher returns, but once the situation reverses, the risk is a price drawdown of over 80% and a recovery period of up to 25 years. “Reflexivity” speculators cannot even wait two or three years, let alone over twenty years?
As for Old Wang Next Door, who claimed to have made thirty times his money, in a future sudden drawdown of over 30%, if he used leverage, he would most likely be liquidated to zero. If he didn’t use leverage, influenced by the “make quick money” mindset, he would feel that the setback was just bad luck and try to recover his losses quickly. But the experience that big drops are followed by rebounds will suddenly fail, and he will face a slow, painful decline until his resources are exhausted.
This brings to mind Schopenhauer’s words: “Those who have had the experience of two or three generations are like people sitting at a magician’s stall at a fair, having watched the same performance two or three times. When the trick no longer feels fresh and can no longer deceive you, its effect is gone.”
Market Analysis: Reflexivity, Cycles, and the Crypto Market’s Next Phase
The latest installment from Wang Chuan offers profound insights that transcend traditional markets, delivering critical lessons for savvy crypto investors navigating today’s frothy landscape. The article’s exploration of reflexivity, narrative migration, and the brutal arithmetic of hardware industry cycles provides an essential framework for understanding where we are in the current crypto cycle and what comes next.
Reflexivity in Crypto Markets
The concept of reflexivity—where asset prices and market psychology reinforce each other in self-perpetuating loops—is perhaps even more potent in crypto than in traditional markets. Crypto markets exhibit extreme reflexivity through:
- Social media amplification: A single tweet can trigger millions of dollars in flows, creating immediate price feedback loops
- Narrative-driven speculation: Crypto’s story-based valuation model creates reflexive dynamics where positive stories attract capital, driving prices higher, which in turn validates the narrative
- Leverage as reflexivity multiplier: The proliferation of perpetual swaps, leverage trading, and yield positions creates reflexive effects where rising prices attract more leverage, which amplifies price movements
This is precisely why we’ve seen such explosive moves in AI-related tokens, RWA (real-world assets) narratives, and L2 scaling solutions. These sectors have been caught in powerful reflexive loops where price appreciation begets more attention, more capital, and further price appreciation.
The Bullwhip Effect in Crypto Infrastructure
Wang’s discussion of the bullwhip effect in hardware industries has direct parallels in crypto’s infrastructure race:
- L2 and scaling solutions: We’re witnessing massive overinvestment in L2 solutions, rollups, and validity rollups. While demand is real, much of it is exploratory and speculative. When the cycle turns, we’ll likely see a brutal shakeout as the supply of solutions vastly exceeds the actual demand for differentiated value.
- Oracle wars: Both Chainlink and Pyth have seen massive capital inflows and valuation expansions. The reflexive nature of this race has driven significant overcapacity, with both projects expanding far beyond near-term revenue requirements.
- Hardware mining: Despite Bitcoin’s predictable halving cycle, the mining industry has experienced brutal drawdowns (2018, 2021-2022) where miners faced insolvency despite the code guaranteeing future block rewards.
The key difference with crypto is that while Bitcoin has a predictable supply schedule, the demand side is far more reflexive and speculative than traditional hardware markets. This creates even more extreme volatility in the valuation of infrastructure projects.
Narrative Migration and Crypto’s “Greater Fool” Problem
Wang’s observation about narrative migration as a recruitment mechanism for finding “greater fools” is particularly applicable to crypto:
- Shifting narratives: We’ve witnessed the rapid migration from DeFi summer (2020) to NFT mania (2021) to L1 wars (2021-2022) to AI+Crypto (2023-2024). Each narrative attracts hot money that quickly migrates when the story loses momentum.
- Valuation decoupling from fundamentals: Many AI+Crypto tokens have seen 10-100x moves based on narrative rather than revenue or user growth. This creates a dangerous situation where valuations depend entirely on the next wave of greater fools.
- The trap of “proof of narrative”: Crypto projects often rely on narrative validation (partnerships, token unlocks, protocol upgrades) rather than fundamental business metrics. When the narrative shifts, these projects can experience 80-95% drawdowns with multi-year recovery periods, if ever.
Asymmetric Risk/Reward in Late-Cycle Crypto
The article’s most critical insight for crypto investors is the changing risk/reward profile as markets mature:
- The “30x” trap: Wang’s example of Old Wang’s 30x return is highly relevant to crypto. Many investors have experienced life-changing returns from early investments in Ethereum, Solana, or other breakout projects. This creates dangerous cognitive biases:
- Equating short-term exponential growth with sustainable moats
- Believing that doubling returns within a year is achievable indefinitely
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Viewing corrections as buying opportunities rather than fundamental reassessments
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Leverage as the accelerant: Reflexive markets are amplified by leverage. The same 30x return that creates psychological comfort could be wiped out by a 30-40% drawdown when leverage is factored in. This is particularly relevant in perpetual markets and yield farming positions.
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The multi-year grind: While Bitcoin has a predictable halving cycle, the recovery for most crypto projects from major drawdowns has taken 3-5+ years, not the 18-month cycles many investors expect. Projects like Cardano, EOS, and many 2017 ICOs still trade below their 2018 highs.
Strategic Implications for Crypto Investors
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Narrative vigilance: Be extremely skeptical of exponential growth claims, especially in reflexive sectors like AI+Crypto. Demand 25-30% annual organic growth, not 300% quarterly jumps that require NDR gymnastics.
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Infrastructure overcapacity: The coming cycle will likely see brutal shakeouts in L2s, oracles, and other infrastructure. Focus on projects with clear product-market fit and revenue diversity, not just narrative momentum.
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Liquidity management: As reflexivity peaks, ensure you have dry powder. The reflexive feedback loops will reverse suddenly, creating asymmetric opportunities for those with cash reserves.
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Time horizons: Align your investment horizon with the project’s actual fundamentals. Most crypto projects require 5-10 years to build meaningful value, not the 3-month cycles reflexive markets suggest.
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Leverage discipline: The reflexive nature of crypto markets means leverage can amplify gains but also create existential risk. Consider deleveraging as reflexivity peaks, even if it means missing further upside.
Conclusion
Wang Chuan’s analysis provides a crucial framework for understanding the psychological and structural dynamics of reflexive markets. For crypto investors, the lessons are clear: we are in a period of extreme reflexivity where narrative, social momentum, and leverage have created a self-reinforcing feedback loop. While this can generate spectacular returns for early participants, the asymmetry in risk/reward intensifies as the cycle matures.
The key to navigating this environment is recognizing when reflexivity has peaked and when the narrative has become decoupled from fundamentals. For those who have profited from recent reflexive moves, the greatest risk may be cognitive—the belief that what worked in the past will continue to work, and that the reflexive feedback will never reverse.
As Schopenhauer noted, when the trick is seen for what it is, its effect is gone. For crypto investors, the challenge is recognizing when the reflexive magic has faded before the music stops.