Global Asset Rotation: Why Liquidity Drives Cryptocurrency Cycles (Part 2)

Introduction: From Macro Theory to Practical Allocation

The first part of this series focuses on building a high-level framework: moving beyond the limitations of cryptocurrencies to understand liquidity as a core driver and anchoring asset behavior to macroeconomic cycles. However, such frameworks often face practical challenges.

Many investors find macroeconomic analysis compelling, yet largely ineffective in practical decision-making. Interest rate, inflation, and liquidity trends seem far removed from everyday portfolio selection. This gap between theory and practice is precisely why most macroeconomic frameworks fail.

The latter half of this series aims to address this deficiency. The key is not to abandon macro thinking, but to refine it by breaking it down into asset classes. Pricing attributes: Which assets are priced globally, and which are priced locally? This distinction determines how capital actually flows and why some markets perform exceptionally well while others stagnate.

Attribute Decomposition: Why Pricing Mechanisms Are Important

After mapping the global asset distribution, the next step is to break down the assets according to their pricing mechanisms. This step is crucial because capital is finite. When funds flow into one market, they inevitably flow out of another.

On the surface, cryptocurrencies seem to have no borders. They trade around the clock, unrestricted by national exchanges or geographical boundaries. However, the funds flowing into the cryptocurrency market are not entirely borderless. These funds originate from specific markets: the US stock market, the Japanese bond market, the European savings market, or emerging market capital.

This presents a significant analytical challenge. While cryptocurrency prices are global, their funding sources are local. Understanding this is crucial. Knowing where the money originates is just as important as understanding why it moves.

This also applies to traditional assets. Stock research must differentiate between US stocks, Japanese stocks, and European stocks. Each type of stock reflects a different economic structure, policy environment, and capital behavior. Only by clearly distinguishing between them can macroeconomic variables play a role.

Why does macroeconomics often feel "useless" in practice?

One reason macroeconomic analysis is often overlooked is that it is perceived as disconnected from practical application. Inflation data and central bank statements often seem abstract and inaccessible when deciding whether to purchase a particular asset.

However, this is not because macroeconomics is unimportant, but because its application is often too broad.

Excess returns do not come from predicting economic growth or inflation in isolation, but from understanding how changes in the macroeconomic environment affect returns. Reallocating marginal capital among competing assets means that market movements depend not on absolute conditions, but on relative attractiveness.

When capital is scarce, it concentrates; when liquidity expands, it searches everywhere. Ignoring this process means passively waiting for the market narrative to unfold, rather than seizing the initiative and leading market trends.

Studying macroeconomic trends allows investors to track the most profitable assets at different times, rather than being trapped in an inactive market waiting for things to improve.

Globally priced assets: One dollar, one market

Some assets are priced globally. The implicit assumption behind this classification is that the US dollar serves as the world's monetary anchor.

Cryptocurrencies, gold, and major commodities fall into this category. Their prices reflect global supply and demand, rather than the situation of any single economy. Whether US dollars flow in from New York or Tokyo, they have the same impact on global prices.

This is significant because the metrics used to analyze these assets highly overlap. Real interest rates, dollar liquidity, global risk appetite, and monetary policy expectations often influence all three simultaneously.

Due to this overlap, globally priced assets are often the most effective targets for macro-driven asset allocation. A proper assessment of liquidity conditions can generate returns in multiple markets simultaneously.

This is the first layer of asset rotation efficiency: understanding when globally priced assets will collectively benefit from the same macroeconomic positive factors.

Stocks as locally priced assets

Stocks are fundamentally different. Stocks represent a claim on the future cash flows of a specific economic entity. Therefore, even in an era of global capital markets, stock prices remain geographically specific.

While global liquidity is important, it is also influenced by significant local factors. Each stock market is affected by its unique combination of structural factors.

The U.S. stock market is influenced by global capital inflows, technological leadership, and the dominance of multinational corporations. Its valuations often reflect not only domestic economic growth but also the ability of U.S. companies to generate profits globally.

Japanese stocks react strongly to exchange rate dynamics, corporate governance reforms, and a prolonged deflationary recovery. Even moderate inflation or wage growth can have a significant impact on market sentiment and valuations.

European stock markets are more sensitive to energy costs, fiscal constraints, and regional political coordination. Economic growth is typically slower, making policy stability and cost structures more significant factors.

Because of these differences, equity investing requires a deeper local knowledge than investing in globally priced assets. Macroeconomic trends lay the foundation, but local structures determine the final outcome.

Bonds are assets priced according to jurisdiction.

Bond markets are more geographically specific. Each sovereign bond market reflects a particular currency, fiscal capacity, and central bank creditworthiness. Unlike stocks, bonds are directly linked to a country's balance sheet.

Government bonds are not just a yield instrument; they are a manifestation of trust: trust in monetary policy, fiscal discipline, and institutional stability.

This makes bond analysis particularly complex. Two countries may have similar inflation rates, but their bond market dynamics can be drastically different due to factors such as monetary systems, debt structures, or political risks.

In this sense, bonds are assets priced according to jurisdiction. Their performance cannot be generalized across markets. Studying bonds requires understanding each country's balance sheet, policy credibility, and long-term demographic pressures.

Summary: Building a Practical Global Framework

By combining the preceding steps with attribute decomposition, a functional global asset framework begins to emerge.

First, we need to build a comprehensive asset map, rather than focusing on just a single market.

Secondly, identify the macroeconomic drivers that can affect all assets simultaneously.

Third, understand where each asset is in the cycle.

Fourth, distinguish between global pricing mechanisms and local pricing mechanisms.

This hierarchical approach transforms macro-analysis from abstract theory into a decision-making tool.

Why Cryptocurrencies Remain the Best Observation Point

While this framework applies to all assets, cryptocurrencies remain a particularly insightful entry point. Because of the lack of cash flow and valuation anchors, cryptocurrencies react more quickly and transparently to changes in liquidity.

Recent market performance clearly demonstrates this. Despite multiple interest rate cuts in the US, cryptocurrency prices have often traded sideways or declined. This has confused many investors, who had assumed that loose monetary policy would automatically push up prices.

The missing link is risk appetite. Interest rate cuts do not guarantee an immediate expansion of liquidity, nor do they ensure that capital is willing to flow into highly volatile assets. There is a crucial difference between existing funds and funds willing to take on risk.

The driving force behind the cryptocurrency bull market is not "excess" money, but rather money that is no longer afraid of a downturn. Liquidity alone is insufficient only when capital shifts from preserving value to speculation.

This also explains why predictions about the future rise of cryptocurrencies are often vague. The issue is not whether loose monetary policy will continue, but when risk tolerance will truly shift.

The true position of cryptocurrencies in global investment portfolios

In traditional financial narratives, cryptocurrencies are often described as "digital gold." But in reality, institutional capital treats them in a very different way.

In actual asset allocation decisions, cryptocurrencies have a low priority. They are neither a core hedging tool nor a defensive asset. They are a form of liquidity at the end of a cycle—more attractive than idle cash, but less trustworthy than almost any other asset.

Understanding this reality is not pessimistic, but rather helps to clarify our thinking. It explains why cryptocurrencies underperform during periods of cautiously loose monetary policy, but experience explosive growth when confidence recovers.

Conclusion: This is just a framework, not a commitment.

Part Two refines the structural foundation of the global asset allocation framework. It offers no shortcuts or guarantees, but rather a perspective to help us understand how capital truly circulates.

By distinguishing between global and local pricing, and recognizing that cryptocurrencies rely on risk tolerance rather than narratives, investors can gain a clearer understanding of where opportunities lie.

The most interesting insights will emerge in later stages—when this framework is applied to real-time data and capital flow signals. These implications will be explored gradually, as value is inherent in the process itself.

The framework is just the beginning; the real work begins with observation.

The above viewpoints are partly referenced from @Web3___Ace