US Dollar Index and Cryptocurrency: What is the Real Signal of the US Dollar Index?

In the past few weeks, I have been delving into a question that initially sounded quite simple: constructing a clearer and more systematic approach to understanding the current state and future direction of the cryptocurrency market. It all started with an article about interest rate cut expectations and their impact on risk assets. After that, I added analyses of stablecoin market capitalization, ETF fund flows, and the U.S. Dollar Index (DXY), among other data. Before I knew it, I realized I had unwittingly fallen into an analysis project that was far more complex than anticipated.

Theoretically, each indicator has a direct economic connection to cryptocurrencies. However, in practice, each indicator has its own timing, volatility, and quirks. They rarely operate independently and can sometimes even contradict each other. The real challenge lies not in understanding the logic behind each indicator, but in how to combine them into a model that reflects reality without being overly simplistic.

To clarify all this information, I categorized these indicators into three types: medium-term indicators, short-term indicators, and long-term indicators. This week, I have been analyzing them one by one.

Medium-Term Indicators: Liquidity Conditions

Stablecoin market capitalization and ETF net fund flows fall under the category of medium-term indicators. They cannot predict what will happen tomorrow, but they can roughly reflect the liquidity environment for the next 1-6 months.

So far, the conclusions drawn have been surprisingly consistent.

The supply of stablecoins has been growing slowly. The growth rate is not rapid, nor has there been any euphoric situation—just a steady increase. This usually indicates that the funds already present in the cryptocurrency market are in a cautious and patient state. They are not in a hurry to sell; rather, they are accumulating strength, waiting for the right moment. This alone is a positive signal.

The total holdings of ETFs also show a similar trend. Since October, total ETF holdings have been declining, but since late November, holdings have stabilized and even shown signs of slight recovery. While this does not mean that "a bull market is coming," it aligns with the expectation that the market is in a mid-cycle correction rather than a macro trend reversal. The current adjustment is far from a true transition to a bear market.

If we stop here, the medium-term outlook appears cautiously optimistic. However, this part of the model is not yet complete. I still need to integrate risk appetite indicators—possibly by tomorrow—only then can the medium- to long-term outlook be sufficiently reliable.

Short-Term Indicators: The Collision of Theory and Reality

Short-term signals are often where the problems lie. The original plan was to focus on the U.S. Dollar Index (DXY), daily ETF net fund flows, and open interest (OI) plus financing amounts. Today, the focus has mainly been on the U.S. Dollar Index.

The concept of the U.S. Dollar Index (DXY) is simple: cryptocurrencies are priced in dollars, so a stronger dollar often negatively impacts risk assets. Additionally, when the dollar strengthens against currencies like the yen or won, investors outside the U.S. find the price of cryptocurrencies relatively higher. The theoretical impact: bearish.

However, when you compare these charts side by side, you will notice subtle differences.

Recently, the movement of the U.S. Dollar Index (DXY) has indeed coincided with local lows in Bitcoin (BTC), but the timing is very close—almost too close to serve as a reliable early warning tool. The definition of short-term indicators dictates that they can only function within a one-month time window, so we cannot expect them to act like precise real-time market signals.

But if we slightly narrow the perspective, DXY becomes easier to understand.

Take the current pullback as an example. The cryptocurrency pullback began around October 8, while the U.S. Dollar Index (DXY) actually issued a warning signal in mid-September. At that time, Bitcoin was trading around $115,000. This gap indicates that the U.S. Dollar Index can lead short-term fluctuations, but its signals are probabilistic rather than absolute.

When we look back at 2022—one of the strongest bear markets in recent years—this example becomes even clearer. The U.S. Dollar Index (DXY) soared for most of that year, while the movement of cryptocurrencies almost completely mirrored it. In this case, the inverse relationship not only worked but also predicted the trend about three months in advance.

However, ironically, this year has been one of the best counterexamples. From January to April, the U.S. Dollar Index (DXY) and Bitcoin (BTC) actually showed correlation, both moving in the same direction for quite some time. If someone relied solely on theory, they would completely misjudge the market.

This leads to the core challenge: any indicator has the potential to fail. When the U.S. Dollar Index (DXY) becomes unreliable, you can still refer to stablecoin supply or ETF holdings. When ETF net fund flows are volatile, open interest (OI) or funding conditions may provide clearer information. The real challenge is not guessing which indicator is "correct," but rather how to appropriately weigh each indicator at a specific moment.

Building a Model That Withstands Real-World Testing

This is why predictive models are elusive. They are not crystal balls, nor do they exist to provide perfect answers. They are frameworks for weighing probabilities. If every indicator always operated as expected, everyone would profit in the same way—the market would cease to function because no one would participate in trading.

A suitable model should neither rely on a single signal nor on rigid mechanical rules. Cryptocurrencies especially require flexibility, as indicators often exhibit asynchronous behavior. When stablecoin supply increases, ETF fund inflows remain neutral, and the U.S. Dollar Index fluctuates wildly, what should be prioritized? When two indicators corroborate each other, but one indicator contradicts both, how do you assess that outlier? These are judgments to be made, not formulaic decisions.

Currently, I have constructed three medium-term indicators and three short-term indicators. Two long-term indicators are still incomplete. Tomorrow, I will finish the missing risk appetite portion, making the medium-term indicator layer more robust. After that, I will gradually refine the long-term and short-term indicator layers until the entire structure forms a coherent and, more importantly, practical system.

Why the Process Is More Important Than the Result

It is clear that the real challenge now lies not in identifying indicators, but in understanding their interactions. Cryptocurrencies are influenced by liquidity, macro expectations, market sentiment, structural flows, and feedback loops. No single number can encompass all these factors.

Interestingly, the more indicators you collect, the more you realize that they do not exist in isolation. They are like pieces of a mosaic puzzle that only make sense when combined. The model I am building will not be perfect—in fact, it shouldn't be perfect. A model that never makes mistakes will never challenge your assumptions and ultimately cannot reflect the real market.

But even if the framework is not perfect, having a structured framework is far better than blindly groping in the dark. When different data points converge, confidence increases; when they diverge, risk awareness heightens. This balance—rather than the accuracy of predictions—is the key to survival in the cryptocurrency space.

Tomorrow, the next piece of the puzzle will be added. Piece by piece, the model will gradually become clearer.

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