Understanding Economics: The Nature of Cognitive Crisis and Uncertainty

December 31, 2025 (1w ago)

TL;DR

When Causal Narratives Fail

We are accustomed to understanding the world through cause and effect. Central bank interest rate cuts lead to stock market rises; geopolitical conflicts erupt, causing safe-haven assets to surge. This linear thinking gives us a sense of control—that as long as we understand the chain of cause and effect, we can predict the future. But the market repeatedly shows us that this sense of control is illusory.

The problem isn't that we occasionally make mistakes in judgment, but that our cognitive models themselves are fundamentally flawed. When market behavior aligns with our expected causal relationships, we're convinced we've found a pattern; when the market deviates, we attribute it to "irrationality" or "emotion"—which is essentially admitting that our causal model has failed, yet we're unwilling to abandon the model itself.

This reveals a deeper cognitive crisis: perhaps we've been looking for the wrong thing from the very beginning. The market may not be a causal system driven by external events, but rather an emergent system in which the interaction of countless actors produces collective behavior that cannot be reduced to a simple causal chain.

The Paradox of Consensus: Self-Realization and Self-Destruction

This leads to one of the most fascinating paradoxes in economics: consensus both creates reality and destroys itself.

When enough people believe that "central banks control everything," this belief becomes a self-fulfilling prophecy—people adjust their behavior according to central bank policies, making it appear as if the central bank truly controls the market. But the stability of this consensus is fragile. Once an event reveals the limitations of central banks (such as their inability to simultaneously control inflation and employment, or their apparent powerlessness in the face of geopolitics), confidence crumbles, and this very collapse accelerates the crisis.

Cognitive biases tell us that the cost of challenging mainstream consensus grows exponentially. But this also means that when consensus collapses, the adjustment is drastic and non-linear. This is why financial markets experience "stampedes"—not because of significant changes in fundamentals, but because of a phase shift in consensus.

So what happens when the consensus that "central banks are omnipotent" begins to falter? We've already seen signs: inflation persisting above target, the failure of negative interest rate experiments, and diminishing marginal utility of quantitative easing. What will be the next dominant consensus? Nobody knows. But what is certain is that the process of consensus transformation is more important than the content of any particular consensus.

Blockchain: More Than Just Technology, It's a Symptom of a Trust Crisis

Re-examining blockchain from this perspective reveals its significance goes beyond mere technological innovation. The core philosophy of blockchain—"the only way to build trust is to trust no one"—reflects a deeper crisis of our time: the collapse of institutional trust.

When people no longer trust central banks, governments, and large institutions to manage money and assets fairly, they turn to algorithms and consensus mechanisms. This is not technological progress, but a desperate innovation—if we cannot trust people and institutions, then trust mathematics and code.

However, this solution is itself full of paradoxes. Blockchain systems still ultimately rely on community consensus, decisions by core developers, and the distribution of computing power among large miners. "Trustless" systems are still built on new trust structures, only these structures are more decentralized and transparent, but not necessarily more robust.

Information Entropy and Markets: Embracing Unpredictability

Traditional economics pursues equilibrium, while modern financial engineering attempts to quantify risk. Both assume that the world can be fully understood and modeled. However, if we rethink it from the perspective of information theory, we arrive at a different picture.

Information entropy measures the uncertainty of a system. A high-entropy state implies more possibilities and a greater potential for surprises. Innovation—whether technological or business model innovation—is essentially a process of increasing system entropy. It disrupts existing equilibrium and creates new possibilities.

This explains why the greatest returns on investment often come from the most unpredictable areas. When a market or industry enters a low-entropy state (highly ordered and predictable), competition squeezes profit margins. Real excess returns come from high-entropy areas—those places filled with uncertainty and avoided by most.

But this also means that the pursuit of certainty may be the biggest risk in investing. When we build sophisticated models and seek "safe" investments, we are actually avoiding uncertainty. In a rapidly changing world, avoiding uncertainty is avoiding opportunity.

A New Cognitive Framework: Coexisting with Uncertainty

Based on these insights, we need a different framework for understanding economics:

  1. Abandon the illusion of linear causality: Acknowledge that markets are emergent systems, and their behavior cannot be simplified to causal chains.

  2. Focus on the consensus transition process: It's not about betting on a particular consensus, but about understanding how consensus is formed, stabilized, and disintegrated.

  3. Treat trust as a variable rather than a constant: The fluctuations in institutional trust are more critical than any single institution.

  4. Embrace high-entropy environments: Seek opportunities amidst uncertainty, rather than avoiding it.

  5. Redefine risk: The biggest risk is not volatility, but a false sense of certainty.

This framework doesn't allow us to predict the future, but it helps us better cope with an unpredictable one. This is perhaps the most honest wisdom economics can offer.

Investment Targets in an Era of Inflation: Thinking Beyond Asset Classes

The Structural Roots of Inflation: More Than Just Monetary Phenomena

Inflation is often simplified to "excessive money supply." But the current inflation cycle reveals deeper structural forces:

Reversal of population structure: Global aging means a shrinking labor supply while consumer demand (especially for healthcare and elderly care) continues to grow. This is a long-term constraint on the supply side.

The ebb of globalization: The deflationary benefits of the past four decades stemmed from the optimization of global supply chains and the rise of China's manufacturing sector. Now, geopolitical risks, supply chain localization, and trade protectionism are reversing this trend.

The cost of energy transition: The transition to clean energy is not simply a matter of technological substitution, but rather a rebuilding of the entire energy infrastructure. The upfront costs of this process are enormous, and will inevitably be reflected in prices.

Return of the wage-inflation spiral: For decades, workers' bargaining power has been suppressed, and wage growth has lagged behind productivity. Now the pendulum has swung to the other side—labor shortages drive up wages, and rising wages drive up prices, creating a self-reinforcing cycle.

Why is it important to understand these structural forces? Because they are not altered by short-term central bank policies. This means that we may have entered a prolonged period of inflationary pressures, rather than a period of short-term cyclical fluctuations.

The Copper Thesis: Opportunities and Pitfalls

Copper is considered a key investment in times of inflation, for good reason: electrification, renewable energy, and electric vehicles all require large amounts of copper. But let's examine this argument critically.

Reasons for support: The increase in global electric vehicle penetration from 5% to 50% signifies an order-of-magnitude increase in copper demand. Each electric vehicle requires four times the copper of a gasoline-powered vehicle. For every doubling of installed capacity for solar and wind power, copper consumption roughly doubles.

Potential risks:

This reminds us that no investment thesis is monolithic. The key is to understand the underlying assumptions of the argument and continuously monitor whether those assumptions still hold true.

Hard Assets vs. Crypto Assets: A Clash of Two Hedging Philosophies

There is a philosophical tension in inflation hedging: do you believe in physical scarcity (commodities, precious metals) or in algorithmic scarcity (crypto assets such as Bitcoin)?

The logic of hard assets: For millennia, gold, silver, and land have served as stores of value because of their physical scarcity and universally recognized worth. Commodities like copper and oil have genuine industrial demand. Inflation erodes the purchasing power of paper money, but it cannot change the scarcity of physical goods.

The logic of crypto assets: In the digital age, value doesn't necessarily depend on physical existence. Bitcoin's 21 million coin cap is algorithmically guaranteed, making it more certain than the geological reserves of gold. Decentralization means it's not controlled by a single country or institution. It's "digital gold," but easier to store and transfer.

The fundamental difference between the two lies in: what is the essence of value? Is it due to scarcity and usefulness in the physical world, or to social consensus and trust mechanisms?

Perhaps the answer is: both are necessary, as they hedge against different risks. Hard assets hedge against inflation within the monetary system; crypto assets hedge against a crisis of confidence in the monetary system itself. If you believe the existing monetary system will continue but currencies will depreciate, buy commodities; if you doubt the long-term stability of the entire fiat currency system, allocate some funds to crypto assets.

Correlation Collapse: Why Diversification No Longer Works

Traditional portfolio theory is based on the assumption that the correlation between different asset classes is stable and low, thus diversification can reduce risk. However, this assumption fails in an inflationary environment.

When inflation becomes the dominant force, almost all risky assets are negatively impacted: stocks fall due to declining earnings expectations, bonds fall due to rising interest rates, and real estate comes under pressure due to rising financing costs. The traditional "60/40" (stock/bond) portfolio is hit simultaneously.

This means we need to rethink the meaning of diversification. It's not simply about diversifying across different asset classes, but rather across different economic scenarios:

True diversification is about diversification across macroeconomic scenarios, not across asset classes.

The Impossibility of "Buy Low, Sell High": The Curse of Psychology

Every investor knows they should "buy low and sell high," especially for highly volatile assets like cryptocurrencies. In theory, investing at the bottom of a bear market, selling at the top of a bull market, and then transferring to stable assets for compound growth—this is the perfect strategy.

But why is it that almost no one can actually do it? Because of the three obstacles inherent in human nature:

Fear: At the bottom of a bear market, everyone is panicking, and mainstream media is filled with the rhetoric of "XX is dead." Buying at this time requires defying the negative information in the entire environment.

Greed: At the peak of a bull market, everyone is celebrating, and the narrative of "this time is different" dominates. Selling at this point means giving up the possibility of further gains, and no one wants to "leave the party too early."

Anchoring effect: People tend to anchor their purchase price to historical highs. In a bear market, the thought is, "Let's wait until we break even"; in a bull market, the thought is, "It's already risen so much, let's wait for it to go even higher."

This reveals the paradox of investing: the best strategies often require counterintuitive execution capabilities. This is why mechanical rules (such as fixed-ratio rebalancing, periodic quotas, etc.) are often superior to subjective judgments—they liberate decision-making from emotions.

Meta-Investment Principle: Invest in Adaptability

Instead of predicting which asset class will outperform, invest in adaptability itself:

Liquidity reserves: Maintaining a certain percentage of cash or cash equivalents is not because of a bearish view on the market, but to ensure that you have the ability to act when opportunities arise.

Cognitive investment: Invest in your ability to understand the world—read, research, and talk to intelligent people. This is the only investment that can transcend all asset classes and market cycles.

Network capital: Invest in relationships and networks of trust. In uncertain environments, the people you can reach, the experts you can consult, and the partners you can collaborate with are more valuable than any asset allocation.

Optionality rather than commitment: In an uncertain environment, maintaining optionality is more important than making irreversible commitments. This means avoiding excessive leverage, avoiding liquidity traps, and avoiding putting all your eggs in one basket.

The Redefinition of Wealth

Finally, a more fundamental question: when the definition of currency itself changes, what does "preserving value" mean?

If the units of value measurement in the future are no longer US dollars, euros, or yuan, but computing power, data, attention, and trust, then the traditional concept of "wealth preservation" may be a false proposition.

Perhaps, what we truly need to preserve is not paper wealth, but rather the ability to create value. Regardless of currency changes or asset fluctuations, the ability to solve problems, create value, and adapt to change is true wealth.

What We'll Need Ten Years from Now: Reflections Beyond the Skills List

Can Old Maps Guide Us to a New World?

We are accustomed to understanding the world by studying history, economics, finance, and psychology. But an uncomfortable question is: are these 19th and 20th-century knowledge frameworks sufficient to understand the second half of the 21st century?

Economics is based on the assumption of scarcity, but artificial intelligence may create material abundance; finance is based on information asymmetry, but blockchain may achieve complete transparency; psychology is based on the limitations of human cognition, but brain-computer interfaces may expand the boundaries of cognition.

This is not to say that traditional knowledge is useless, but rather that we need to maintain cognitive openness. When studying economics, one should also ask: Does supply and demand theory still apply when marginal cost approaches zero? When studying finance, one should also ask: How will the market microstructure change when assets can be traded programmatically?

Ten years from now, what we may need is not a specific knowledge system, but the ability to learn and discard knowledge—knowing when to use the old framework and when to create a new one.

Specialization vs. Generalism: A False Dichotomy

There is a classic dilemma in career development: should one specialize in one field to become an expert, or should one broaden one's knowledge to become a generalist?

However, this might be a flawed framework. Truly high-value roles are often "T-shaped talents"—deep in one field but broad in multiple related fields. Or, going a step further, "π-shaped talents"—deep in two different fields, capable of connecting different knowledge domains.

Why? Because innovation often occurs at the boundaries. When you have a deep understanding of field A and sufficient knowledge of field B, you can see connections that others cannot. Fintech comes from the intersection of finance and technology, behavioral economics from the intersection of economics and psychology, and synthetic biology from the intersection of biology and engineering.

So the question isn't "specialization versus generalism," but rather: at which intersections can I create unique value?

The Trap of Compound Interest: When Optimization Becomes Vulnerability

We've all heard the myth of compound interest: improve by 1% every day, and after a year you'll be 37 times your original value. This motivates us to pursue continuous optimization, maximize efficiency, and eliminate waste.

However, this mindset is dangerous. Over-optimization can lead to vulnerabilities:

Path dependency: Compound interest requires continuous positive accumulation. However, if you're going in the wrong direction, compound interest can lead you further and further down the wrong path.

Lack of exploration: When you focus on optimizing a known domain, you miss out on greater, unknown opportunities. This is known as the "local optimum trap."

Black swan vulnerability: Highly optimized systems often lack redundancy. Even a small shock can cause the entire system to crash.

This means that we need to find a balance between commitment and optionality. Yes, specializing in one area can bring compound interest; but leaving room to explore other possibilities will prevent you from getting locked into a suboptimal path.

Specifically: Reserve 20% of your time and resources for exploring, experimenting, and learning things that are unrelated to the main topic. This is not a waste, but rather reserving options for the future.

The Future of Blockchain: Not in Price, But in Institutions

Cryptocurrency investors focus on price. But a more interesting question is: what will happen when sovereign wealth funds start allocating to Bitcoin, central banks issue digital currencies, and traditional financial institutions fully embrace blockchain?

This is no longer a technical issue, but an institutional evolution question. The history of currency is essentially the history of institutions—from shells to gold, from paper money to electronic currency, each transition has been accompanied by a reorganization of power structures.

The revolutionary nature of blockchain is not in the technology itself, but in the radical question it poses: can we coordinate large-scale economic activity without centralized authority?

In the next decade, this experiment will unfold at various levels: decentralized finance (DeFi) challenges traditional banking, decentralized autonomous organizations (DAOs) challenge corporate governance, non-fungible tokens (NFTs) challenge intellectual property rights.

The focus should not be on "how much a certain coin will rise," but rather: which institutional innovations truly solve real problems and gain sustainable adoption?

Career Choice: From Skills to Problems

"What skills should I learn?" This is the wrong question. Skills become obsolete, but problems do not.

A better question is: what problem am I willing to dedicate ten years to?

If you're obsessed with energy efficiency issues, you might become a clean energy engineer, a carbon market trader, or a climate policy expert—the specific career may change, but the core problem remains.

If you're obsessed with information asymmetry issues, you might become an investigative journalist, a data scientist, or a market designer—different forms, but the same essence.

Live for the problem, not for the career.This way, when technology and industries change, you won't lose direction—because the problem remains, you're just finding new ways to solve it.

The Philosophy of Three Dependencies: Sustainable Motivation

People need three things to live: a dependency, an expectation, and a tomorrow. This is not just feel-good advice, but a profound psychological insight.

Dependency: What is a certain anchor point in your life? It might be family, community, faith, or habits. This gives you stability.

Expectation: What do you specifically look forward to in the near future? It might be the completion of a project, a trip, or mastering a skill. This gives you direction.

Tomorrow: What vision do you have for the long-term future? It might be a goal you want to achieve or a life you want to live. This gives you meaning.

All three are indispensable. With only dependency, life becomes repetitive day after day; with only expectation, you fall into short-termism; with only tomorrow, you lose motivation because it's too distant.

Sustainable motivation comes from the balance of these three: grounded dependency, clearly visible expectations, and a tomorrow worth pursuing.

A Critique of "Follow Your Passion"

Steve Jobs said: "Find what you love." This quote has inspired countless people, but also misled countless others.

The problem is that most people don't know what they truly love. How can you love a field you've never deeply understood? Passion is often not the starting point, but the result—when you invest enough in a certain field and gain a sense of achievement and control, passion emerges.

Perhaps more honest advice is: find a field you're willing to endure frustration for. Any field is difficult when you go deep; the key is what you're willing to endure those difficulties for?

Following your passion sounds beautiful, but cultivating passion may be more realistic. Choose a promising direction, invest enough time and effort to achieve some degree of mastery, and passion will grow in that mastery.

Decision Framework: Moving Forward in the Fog

Synthesizing these reflections, how do we make decisions when the future is full of uncertainty?

A viable framework is the "minimum regret principle": Don't ask "what will make me most successful," but rather "what will make me least regretful."

Ten years from now, what are you more likely to regret:

Regret minimization doesn't equal risk aversion. Sometimes the biggest regret comes from being overly cautious. But it does require you to honestly face what you truly care about.

Another principle is "reversibility first": When facing uncertainty, prioritize reversible decisions. Learning a new skill is reversible (if it's not suitable, you can pivot), but signing a 20-year mortgage is not; joining a startup is reversible (if it doesn't work, you can leave), but having children is not.

This doesn't mean avoiding all irreversible decisions, but rather: for reversible decisions, be bold and fast; for irreversible decisions, think deeply and carefully.

Conclusion: Uncertainty as a Condition of Existence

From economic cognition to investment strategy, from career planning to life philosophy, one theme runs throughout: we live in a fundamentally uncertain world.

This is not pessimism. On the contrary, uncertainty is the premise for the existence of opportunity. If everything were predictable, there would be no room for excess returns; if everything were determined, there would be no meaning to choice.

What we need is not to eliminate uncertainty (which is impossible), but the wisdom to coexist with it:

Ten years from now, where will the market be? Will inflation persist? Which technology will dominate? We don't know.

But we know: regardless of how the future changes, those who can learn quickly, adapt flexibly, and create value for real problems will find their place.

Ultimately, this is not about predicting the future, but about being prepared to embrace an unknown future. As the saying goes: accept fate gracefully, cherish connections, but don't cling. Stay open, stay curious, stay active.

This may be the wisdom of our generation: move forward with determination in the fog, creating certainty within uncertainty.

kkdemian
hyperliquid