Has the Macroeconomic Pricing of BTC Changed? A Nine-Year Review of the Federal Reserve, the Dollar, the Nasdaq, ETFs, and Stablecoins

From the Federal Reserve, the Dollar, and the Nasdaq to Stablecoins: BTC is becoming an increasingly complex asset

Written by: Fu Gui

Staring at a switch for too long can make one think that it controls all the lights. We have been focused on the Federal Reserve for nine years, almost forgetting that BTC is no longer just connected to it. It wasn't until I re-ran the data from the past nine years—2438 trading days and 62 FOMC meetings—that I realized: it hasn't decoupled from the Federal Reserve; it has just changed its connection method.

Interest Rates Increased, BTC Didn't Crash; After a Year of Easing, BTC Dropped by 38%

On September 16, 2026, the Federal Reserve held a meeting that made many people nervous. The federal funds rate was raised by 25 basis points to 3.75% to 4.00%. This was the first rate hike in three years since July 2023. It passed unanimously with 12 votes in favor and 0 against. In the first meeting after the new chair, Waller, took office, the dot plot indicated that most officials expect another hike within the year.

Crypto Twitter immediately echoed familiar slogans: rate hikes, tightening liquidity, risk assets will fall, BTC is doomed.

However, upon checking the market, BTC did not experience a typical "policy shock crash" immediately after the announcement. But this is not the most interesting part of this article. What is truly worth studying is: how does the Fed's influence on BTC prices manifest when we extend the time frame to days, weeks, or even years?

If a formula has been useful for nine years but seems to malfunction now, either the button is broken, or the wiring has been altered.

To clarify this matter, I re-ran the data from January 2017 to September 15, 2026. Over 2438 trading days and 62 FOMC meetings, I used the daily closing price of BTC/USD from Coinbase on FRED, with all macro variables sourced from FRED's official series, and stablecoin data from DefiLlama. It should be noted that the data is up to September 15, 2026, and the details of the market on September 16 are not part of this sample and are outside the scope of this validation. The results indicate that it is not that "BTC is unaffected by the Federal Reserve," nor that "BTC has completely decoupled," but rather a set of facts that are more complicated than either of these.

Before delving into these facts, let's present a larger paradox.

Before the rate hike on September 16, for a whole year—from October 2025 to September 2026—the actions of the Federal Reserve had nothing to do with "tightening."

The Formula "Rate Cuts and Easing Lead to BTC Increases" No Longer Works

Let's look at a set of numbers.

From October 6, 2025, to September 15, 2026, during these 237 trading days, the effective federal funds rate dropped from 4.09% to 3.63%, a decrease of 46 basis points. The Federal Reserve's balance sheet expanded from $6.59 trillion to $6.74 trillion, an increase of $150 billion. The year-on-year growth rate of M2 rose from 4.19% to 4.59%, and net liquidity improved from -6.74% to +2.02%. During the same period, the Nasdaq 100 rose by 16.8%, and the S&P 500 increased by 13.0%.

According to the old script, this is called "full easing." Easing should lead to increases, and the more liquidity, the stronger the rise.

However, BTC dropped from $124,000 to $75,000 during this time, a decline of 38.2%.

Liquidity was increased, the stock market rose, yet the asset that had consumed the most liquidity over the past decade fell by nearly 40%.

This cannot be explained by a mere "short-term fluctuation." In the fourth quarter of 2025 alone, BTC fell by 26.09%, while the S&P rose by 2.35%, and the Nasdaq increased by 2.31%. M2 decreased from 4.48% to 3.96%, the Federal Reserve's assets grew from $6.59 trillion to $6.64 trillion, and the federal funds rate dropped from 4.09% to 3.64%—a rate cut of 45 basis points. Both rate cuts and balance sheet expansion were present, yet BTC did not rise.

More critically, there was a reversal in frequency. When aligning BTC's year-on-year return with M2's year-on-year growth rate, during phase P1, which is from March 2020 to March 2022 (zero interest rate plus QE), the correlation coefficient was 0.716, indicating a strong positive correlation. In phase P2, the aggressive rate hike period, it was 0.520, still positive. By phase P3, the high interest rate period from July 2023 to now, this number flipped to -0.766. When M2 was expanding rapidly, BTC was actually falling.

I must apply the brakes here. This is not to say that liquidity is unimportant. On a level basis, M2 and BTC appear highly correlated, but the Engle-Granger cointegration test tells us that ln(BTC) and ln(M2) do not have a cointegration relationship across the three phases, with a p-value of 0.729—indicating that the two series, each with its own trend, happen to move together, and there is no long-term equilibrium relationship. The high R-squared obtained from regressing on level values is a spurious regression. The "easing leads to increases" principle has already ceased to be a cross-cycle rule in phase P3.

Does this mean that the Federal Reserve can no longer influence BTC?

It's Not That They Can't, It's That They Are Observing from the Wrong Window

Looking at daily returns, the relationship between interest rate changes and BTC is surprisingly weak. In the full sample daily frequency regression, the correlation coefficient between M2's month-on-month change and BTC's daily return is -0.036, with the highest in the three phases being only 0.031; the year-on-year change of the Federal Reserve's balance sheet and BTC's daily return is -0.029, and not significant in any phase. The daily change in the federal funds rate has a correlation coefficient of -0.001 with BTC's daily return across the full sample. It indeed appears as if they have decoupled.

However, there is an issue with the observation frequency. Looking solely at daily returns means mixing all directional signals into one pot—expected rate hikes, unexpected hawkishness, unexpected dovishness, and ordinary days with no news, all combined to calculate a single correlation coefficient. Positive and negative signals dilute each other, and it naturally appears that there is no relationship.

I isolated the FOMC meeting days to conduct an event study. The average daily change in the 2-year Treasury yield on FOMC days is 6.34 basis points, while on non-FOMC days it is 3.89 basis points, with a significant difference (p=0.0015). I did not directly use high-frequency target/path surprises but instead used the change in the 2-year Treasury yield on FOMC days as a daily frequency proxy variable for monetary policy shocks. It should be noted that the 2-year yield includes not only changes in monetary policy expectations but also inflation expectations, growth expectations, term premiums, information from the press conference, and other macro news from that day; it is a proxy variable rather than a clean policy surprise. The subsequent "shock" refers to the tightening monetary policy shock characterized by this proxy variable. I then used Jordà's (2005) local projection method to estimate for each horizon h—i.e., the h-th trading day after the FOMC—cumulative returns from the day before the FOMC meeting to h days later, regressing against the monetary policy shock characterized by the 2-year yield.

In other words, I am no longer asking, "How much did BTC drop today after the rate hike?" but rather, "What happened to BTC in the next 1 day, 3 days, 10 days, 20 days, and 30 days after a tightening monetary policy shock?"

The results are completely different.

According to the daily frequency definition of this article, the cumulative response of BTC on FOMC trading days is close to zero. At h=0, β is -0.11%, with a t-value of -0.29, statistically indistinguishable from zero. Here, I must actively disclose a methodological limitation: the FOMC statement is released at 14:00 Eastern Time, while BTC trades 7×24 hours. The daily closing prices from FRED cannot strictly identify the immediate high-frequency response after the announcement—meaning that the "h=0 shows almost no response" refers to no significant response within the daily event window, rather than indicating that the market had no reaction at all in a high-frequency sense. The "Bitcoin-Macro Disconnect" mentioned in the New York Fed's staff report SR1052 is based on intraday event studies, and their conclusion is that BTC does not significantly respond to macro news during the sample period. The h=0 results under the daily frequency scope of this article align with their direction but cannot be directly equated.

However, as we extend h further. At h=1, BTC is still almost unchanged, at -0.03%. At h=5, it is -1.43%. By h=10, the cumulative negative response reaches -2.60%, with a t-value of -1.88, marginally significant. This magnitude is 3.7 times the -0.70% of the Nasdaq during the same period and 5.8 times the -0.45% of the S&P. Then at h=20, it returns to -1.22%, and at h=30, it further drops to -0.54%.

It is not that there is no response; rather, the response is slow and significant.

Next, let's examine the subsample after the ETF listing. After the approval of the spot ETF on January 11, 2024, there have only been 21 FOMC meetings, which is a small sample. I must clarify that these coefficients are directional evidence, not precise estimates, and the subsequent precise numbers should not be overstated. However, the direction is very clear: before the ETF, BTC's response to tightening policy shocks across all horizons was positive and not significant, with h=30 even at 0.683, essentially immune. After the ETF, the negative impact monotonically amplified with the time horizon, with h=1 at -0.182, h=3 at -0.403, h=7 at -0.687, h=14 at -0.857 (t=-2.53), and h=30 at -1.063 (t=-2.07). The 30-day effect is 5.8 times the 1-day effect.

This is not a liquidity liquidation that flashes and then recovers on the announcement day; it resembles a revaluation—markets take several weeks to slowly digest a tightening policy signal.

The Federal Reserve does not issue a "buy or sell order" to BTC. It is more like throwing a stone into the financial system, with ripples spreading outwards.

Bonds Hear First, Stocks Follow, BTC Last, But Drops the Most

Let's rank the response times of various assets to the same tightening monetary policy shock.

On the first trading day, the yield on the 10-year U.S. Treasury bond rose significantly by 1.71 basis points, with a t-value of 2.46, making it the only asset in the full sample to reach significance at h=1. The bond market priced this in first, which is the first layer in the textbook.

About the 20th trading day, or roughly a month later, the Nasdaq 100 and S&P 500 reached statistical significance— the Nasdaq fell by 0.82% (t=-2.16), and the S&P fell by 0.55% (t=-2.26). This is the second layer in the stock market.

BTC reached its response peak at h=10, with a negative amplitude of 2.60%. Its response timing is sandwiched between the bond and stock markets, but the amplitude has been amplified several times.

What about the U.S. dollar index? The absolute t-values for all 8 horizons from h=0 to h=30 are less than 1, with a maximum of only 0.97, indicating no significance at all.

To illustrate, imagine a shopping mall suddenly losing power. The first to know are the distribution room staff; the current is cut off, and the surveillance system immediately alarms. Then the merchants on each floor notice the lights go out, and chaos ensues. Finally, it is the people in the parking lot preparing to leave who get the news last— they may be slow to react, but the stampede at the exit is the worst.

BTC is somewhat like that parking lot. It is not the first to receive the news, but the final crowding and stampede are the most severe.

An exploratory Baron-Kenny mediation analysis also provided clues in the same direction. In the contemporaneous dimension at h=0, the Nasdaq is the only significant candidate mediating variable, with a t-value of 2.35 and a p-value of 0.022— after controlling for the Nasdaq, the direct effect of the 2-year interest rate proxying the policy shock on BTC decreased from -0.107 to -0.071, a reduction of 34%. The dollar as a mediator is not significant, with a t-value of -1.63 and a p-value of 0.109, even showing the opposite direction from what was expected. This only indicates that the contemporaneous statistical relationship is compatible with the "equity market channel" and cannot independently prove a causal transmission chain; mediation analysis here is affected by contemporaneous correlation, omitted variables, measurement errors, etc., and can only serve as directional reference.

The Dollar and BTC Often Move in Opposite Directions, but the Fed Does Not Rely on the Dollar to Communicate

The most widely circulated image in the crypto circle is: when the Fed raises interest rates, the dollar index DXY rises, and BTC falls. The chain is simple and looks smooth.

But here we need to distinguish between two different issues.

The first question is whether "the dollar and BTC often move in opposite directions." The answer is affirmative, and it is one of the most stable simple macro relationships across cycles. The full sample daily frequency correlation coefficient is -0.197, with three phases showing -0.236, -0.281, and -0.097, all significant. Regardless of whether it is during the QE period, the rate hike period, or the current high period, a strong dollar suppresses BTC, although the degree of pressure varies.

The second question is whether "the Fed transmits policy shocks to BTC through the dollar." There is no support for this in the event study framework. As mentioned earlier, all horizons of DXY's response to tight monetary policy shocks within 30 days after the FOMC are not significant— the Fed throws a tight stone, and the dollar index does not ripple at all.

There is a more detailed reversal in the mediation analysis that deserves separate mention.

Before the ETF listing, the Fed influenced BTC mainly through the dollar. Tight policy shocks pushed up DXY (a=+4.29, t=4.87), and a strong dollar depressed BTC (b=-0.035, t=-3.60), with an indirect effect of -0.152. During the same period, the U.S. stock channel was completely cut off— the Fed's shock did not affect the Nasdaq in the event window, and the Nasdaq did not predict BTC either.

After the ETF listing, this leg was broken. Tight policy shocks still pushed up DXY (a=+3.73, t=2.46) and real interest rates (a=+0.296, t=2.70), and the Fed's influence on traditional macro variables remained unchanged. However, the marginal effect of DXY on BTC dropped from -0.035 to -0.002, nearly zero, and the indirect effect shrank to -0.007. Meanwhile, the direct channel from the Fed to BTC opened up, with a total effect of -0.182 and a p-value of 0.054— indicating the existence of a direct pathway that does not go through the dollar, the Nasdaq, or real interest rates.

"The dollar and BTC often move in opposite directions" is a fact. "The Fed transmits shocks to BTC through the dollar" no longer holds after the ETF. These two statements are not contradictory.

What Changed After the ETF

Everyone thought the ETF would send BTC to Wall Street, making it a more standard tech stock. The story told by the data is more complex.

First, there is a place that must be honestly addressed. If we regress BTC daily returns against SP500 daily returns, using January 11, 2024, the ETF listing date as a breakpoint for Chow structural tests, the F-value is 1.51, and the p-value is 0.221— strictly speaking, we cannot reject the null hypothesis of "structural stability." The β estimates for the two segments are both noisy: before the ETF, β=-0.130 (t=-1.41), and after the ETF, β=+0.178 (t=1.45), neither significant. We cannot directly attribute the statement "β dropped from 0.789 to 0.417, a 47% statistically significant decline" to the SP500.

For the Nasdaq 100, performing the same test, the interaction term regression shows that β dropped from 0.789 to 0.417, with an interaction term t-value of -2.70 and a p-value of 0.0071; the Chow F-value is 3.944, with a p-value of 0.0195, which is statistically significant. However, it is important to note that the sample starting point for the Nasdaq 100 is different, and the annual β is highly non-monotonic— in 2019, β was still -0.371, during the aggressive rate hike period in 2022 it peaked at 1.176, and in 2023 it fell back to 0.481, dropping to 0.005 in 2025, nearly zero, before returning to 0.805 in 2026. This is not a stepwise change where "β drops immediately after the ETF listing."

The truly statistically stable structural changes are the following three.

First, there is a systematic reduction in volatility. The annualized volatility of BTC dropped from 75.1% before the ETF to 48.5% after the ETF, a reduction of about 35%. This is the hardest number, with no dispute over direction or magnitude. Retail noise has decreased, and pricing has begun to normalize.

Second, the one-day leading effect of U.S. stocks on BTC has strengthened. The cross-correlation function shows that the previous day's returns of the SP500 predict the current day's returns of BTC, increasing from 0.255 before the ETF to 0.379 after the ETF, with a stable peak at lag=+1. This corroborates Mohamad's (2025) finding that "the ETF dominates BTC price discovery about 85% of the time"— the price discovery efficiency of the U.S. stock market is higher, with macro information priced in the U.S. stock market first, then transmitted to BTC through the ETF funding channel.

Third, the 90-day rolling average correlation between BTC and SP500 rose systematically from 0.002 before the ETF to 0.062 after the ETF, with a Welch t-value of -11.14 and a p-value of less than 0.001. The correlation co-movement has indeed statistically increased, but the magnitude of the increase is still far from making "BTC become like the Nasdaq."

Looking at these three changes together, the direction is consistent: after institutional entry, the flow of information between BTC and U.S. stocks has accelerated, price discovery has become more synchronized, and pure speculative noise has decreased. However, this does not mean that BTC has become a high Beta tech stock, nor does it mean that the Nasdaq can explain most of BTC's volatility— after the ETF, the R² of the single-factor regression of the Nasdaq 100 on BTC is only 0.035, meaning the Nasdaq can explain less than 4% of BTC's volatility.

Another thing contradicts the intuition that "BTC has become more like a stock." As mentioned earlier, after the ETF, BTC's negative response to tight monetary policy shocks began to accumulate continuously over a 2 to 4 week scale, with a 30-day β of -1.063— its sensitivity to macro policy signals has shifted from "basically immune" to "delayed but continuously repriced."

These two things can coexist. BTC can be more sensitive to the Fed's shocks, while not completing pricing instantaneously like the Nasdaq on FOMC days. This is because macro sensitivity and stock Beta are fundamentally different concepts. The former refers to whether "policy shocks will eventually reflect in prices," while the latter refers to "how synchronized BTC is with the Nasdaq's daily ups and downs." After the ETF, the former is accumulating, while the latter is decreasing.

It Is Not the Fed Leading BTC, Many Times BTC Sees Danger First

When conducting Granger causality tests, I saw the most surprising set of numbers in the entire study.

For daily returns with a lag of 5 periods in P1, which is the zero interest rate and QE period from March 2020 to March 2022, the statistically significant direction is that BTC leads macro variables, not the other way around. BTC leads the S&P 500, with a p-value of 0.0015; BTC leads VIX, with a p-value of 0.0001; BTC leads the dollar index, with a p-value of 0.018; BTC leads the 10-year real interest rate, with a p-value of less than 0.0001. The Nasdaq in P1 shows a bidirectional relationship, with BTC leading the Nasdaq at p-value 0.012, and the Nasdaq leading BTC also at 0.042.

In P3, which is from July 2023 to now, this direction reappears overwhelmingly. BTC leads the S&P 500, with a p-value of less than 0.0001; BTC leads the Nasdaq 100, with a p-value of less than 0.0001; BTC leads VIX, with a p-value of less than 0.0001. The direction from macro variables to BTC is not significant during this phase.

Only in P2, which is the aggressive rate hike period from March 2022 to July 2023, did we see the true "macro variables leading BTC"— the 10-year U.S. Treasury yield to BTC, with a p-value of 0.0089; the 10-year real interest rate to BTC, with a p-value of 0.049. This is the only time in the entire sample where BTC was led by interest rates.

Granger causality is not economic causality; it refers to the temporal predictive lead— whether the historical values of X can help predict the future values of Y, providing more information than just looking at Y's own history. Moreover, part of the lead may come from BTC trading 24/7, while U.S. stocks and the bond market only operate during weekdays; events occurring in Asia and on weekends are priced in by BTC first, with U.S. stocks catching up when they open. This mechanical lead caused by trading time differences exists, and common shocks (both markets responding simultaneously to some unobserved third factor) cannot be ruled out through Granger tests.

However, even if these points are clarified, the result still overturns a popular narrative. Most analysts focus on the Federal Reserve and liquidity data to predict BTC. Data shows that, except for the aggressive rate hike period in 2022, the statistical basis for this "macro prediction of BTC" is thin; conversely, BTC's price movements often statistically precede changes in macro sentiment indicators like VIX, S&P 500, and NASDAQ. It resembles a canary that might chirp early—when the gas concentration in the mine rises slightly, it might tilt its head first; but this "early" is a statistical lead, not implying that BTC has truly "seen" the future, nor can it exclude the leading effects caused by common shocks and the 7×24 hour trading structure. By the time traditional indicators signal an alarm, it is sometimes already a beat late, and sometimes it is just BTC's own noise.

This does not contradict the earlier statement that "BTC is the last layer of the transmission chain." The two statements refer to different dimensions: in the FOMC event window, identifying causal shocks, BTC indeed completes its repricing after the bond and stock markets; but in the daily time series without obvious policy events, BTC, due to its around-the-clock trading and sensitivity to sentiment, has priced in implicit risks ahead of traditional markets. One is about "how policy shocks transmit," and the other is about "who perceives risk appetite first."

A Portion of BTC's Money Has Already Stayed in Crypto

Earlier, it was mentioned that no cointegration relationship was found between M2 and BTC across three phases, with a p-value of 0.729. Applying the same test to stablecoins yields completely different statistical properties. The Engle-Granger cointegration test statistic for ln(BTC) and ln(total market cap of stablecoins) is -4.160, with a p-value of 0.0042—indicating a statistical long-term equilibrium relationship between the two. This suggests that there may be a more stable long-term co-movement between stablecoins and BTC than with M2, but it does not itself prove a causal relationship. Cointegration may arise from common market size growth, expansion of the Crypto ecosystem, and adoption trends, and one cannot conclude that "stablecoins drive BTC."

The year-on-year changes are steeper. The year-on-year correlation between stablecoins and BTC: in 2024, it is -0.007, almost zero correlation; in 2025, it rises to 0.312; in 2026, it reaches 0.743; and in the most recent year, the rolling correlation has reached 0.891. In contrast, during the same period, the year-on-year correlation between M2 and BTC in P3 is -0.766—two liquidity indicators, one traditional M2 and one Crypto's own stablecoin, giving completely opposite signals. The cointegration test pertains to stablecoins.

I must also clarify the other side; I cannot only highlight the attractive numbers. On a weekly frequency, the relationship between stablecoins and BTC is weak and unstable. The correlation coefficient between weekly changes in stablecoins and weekly returns of BTC is only -0.093, and the Granger causality from stablecoins to BTC at the weekly frequency has a p-value of 0.0569, which is not significant; leading-lagging scans show a leading correlation of 0.201 when lagged by 5 weeks, indicating that BTC leads stablecoins. The correlation coefficient between the 30-day growth rate of stablecoins and daily returns of BTC is only -0.033—Oefele (2025) also found that ETF fund flows are a result of price rather than a cause; funds come in only after prices rise, showing clear reverse causality.

This means that stablecoins are not a short-term trading signal. One cannot judge whether BTC will rise or fall tomorrow based on how much stablecoins were issued today. They resemble a slow variable, determining the valuation center rather than intraday fluctuations.

What truly carries information is state-dependent regression. I grouped the samples by the growth rate of stablecoins; when stablecoins are in a high expansion state, the β of BTC and the S&P 500 is -0.220, with a t-value of -2.10, indicating a significant negative correlation—BTC will move in the opposite direction to the U.S. stock market in this state, following its own independent trend. When stablecoin growth stagnates, BTC only weakly follows the U.S. stock market (β=+0.082, not significant).

This is the core concept of the entire text. BTC is now facing two liquidity systems simultaneously.

One is the liquidity of traditional finance—Federal Reserve interest rates, M2, the U.S. dollar, and U.S. stock market risk appetite. This system influences BTC through ETF funding channels and institutional cross-asset allocation. The other is Crypto's own liquidity—expansion and contraction of stablecoins, inflows and outflows of on-chain funds, and internal risk appetite within Crypto. This system circulates independently outside the traditional framework.

The paradox from October 2025 to September 2026 finally has a resolution. Liquidity has been released, but it is the liquidity from the Federal Reserve; when BTC fell, the total market cap of stablecoins did not shrink in sync, but continued to expand—from over 300 billion to over 310 billion, setting a historical high. This at least indicates that the price drop of BTC did not coincide with the simultaneous disappearance of Crypto dollar liquidity, suggesting a potential divergence in the rhythm of traditional liquidity and internal Crypto liquidity. However, this cannot be simply interpreted as "money not leaving Crypto"—stablecoins can remain in on-chain wallets, be held on exchanges, placed in DeFi, buy government bonds (RWA), be idle, held by arbitrage institutions, or transferred internally within institutions. The expansion of the total market cap of stablecoins only indicates that the supply of stablecoins has not shrunk in sync, not that all funds are waiting to buy BTC. The BIS working paper WP1219 found that after tightening, the market cap of stablecoins decreases while the AUM of money market funds increases, indicating a direction opposite to traditional liquidity, suggesting that the response of stablecoins to monetary policy is itself slow and cumulative, not something observable in the event window within 30 days after the FOMC.

So What Exactly is BTC?

It is not digital gold. On the five trading days with the most significant jumps in VIX, the average returns of BTC across three phases are all negative, with a probability of decline exceeding two-thirds; during the aggressive rate hike period in P2, the probability of a simultaneous drop is 88.9%, with an average drop of 5.67%. When panic strikes, it does not serve as a safe haven; it falls along with the market, and even more severely.

It is also not another NASDAQ. After the ETF, the single factor of NASDAQ 100 can only explain 3.5% of BTC's volatility; in the first quarter of 2025, BTC and NASDAQ were even significantly negatively correlated (β=-0.377, t=-2.47).

A more accurate statement is that it has four faces, and which face is revealed depends on the current state.

When faced with a tightening policy shock from the FOMC, it acts as a macro risk asset. After the ETF, tightening policy signals will continue to accumulate over the following weeks, suppressing its price, with a 30-day cumulative effect of about 1%. However, it does not complete pricing within half an hour like the NASDAQ; instead, it takes several weeks to slowly reassess.

When the market is in extreme panic and VIX soars, it acts as a high Beta amplifier. During the worst 5% of days for the S&P in the P2 phase, BTC's decline is 2.69 times that of the S&P itself; the left-tail β from quantile regression is 2.391, which is 2.2 times the median β. During declines, it follows most closely and falls the hardest.

When stablecoins are rapidly expanding on-chain, it acts as an endogenous asset of Crypto, decoupling from U.S. stocks, with β at -0.220, following its own trend. At this point, traditional macro analytical frameworks become largely ineffective.

On ordinary days without obvious policy shocks, it occasionally plays the role of a canary for global risk appetite—its 7×24 hour pricing allows it to respond to implicit risks ahead of U.S. stocks and VIX in many instances, especially during QE periods and in the P3 phase where Granger leading is significant.

The four faces are not mutually exclusive; they coexist simultaneously, but which one is illuminated at the moment depends on volatility, trends, the state of stablecoins, and whether it is FOMC week, with a host of state variables determining the outcome.

So, when you see statements like "the Federal Reserve has cut interest rates, BTC should rise," it is best to first ask yourself three questions. First, has this rate cut already been priced in by the market, and what is the direction of the unexpected part? Second, what is the current state of traditional assets—has the bond market moved, has the stock market moved, and what is the position of VIX? Third, what is happening within Crypto's own funding pool—are stablecoins expanding or contracting, and is the on-chain sentiment hot or cold?

Building an observation framework with four layers is much more useful than just focusing on an interest rate button: tightening monetary policy signals first affect bonds and real interest rates, then influence stock risk appetite, and finally overlay the direction of internal Crypto liquidity, before finally landing on BTC. Each layer has the potential to block, delay, or even reverse the effects.

The Question Was Wrong

For the past few years, everyone has been asking one question: Is BTC a macro asset?

This question itself is wrong.

The real question should be: Under what conditions is BTC what kind of asset?

During the QE liquidity release in 2020, it could act like a liquidity-driven risk asset, positively correlated with M2 at 0.716, rising along with the liquidity. During the aggressive rate hikes in 2022, it became a high Beta risk asset, correlated with NASDAQ at 0.506, being driven by interest rates, with the 10-year yield and real interest rates Granger leading it. After the ETF listing in 2024, its pricing microstructure changed, information flow became faster, and volatility decreased, but it did not become like NASDAQ; instead, in 2025, it was significantly negatively correlated with NASDAQ. By 2026, the liquidity of stablecoins within Crypto established a cointegration relationship with it, with a year-on-year correlation of 0.743, and external macro Beta and internal funding Beta began to run in parallel.

The reason the rate hike on September 16 did not trigger a typical policy shock flash crash is not that BTC has detached from the macro—according to the data in this article, BTC's typical response pattern is not "falling on FOMC day"; if a real response occurs, it would slowly emerge over the next two weeks to a month (current sample data suggests this may be the case). More importantly, a full year before the rate hike, the market had just educated everyone with a 38% drop: the simple formula of "liquidity must rise" is no longer effective. The script for September 16 did not follow the old version; in fact, the old version had already begun to fail a year ago.

BTC's Beta itself is a variable. It is not a constant, not a fixed label, and not a one-way trend of "becoming more like U.S. stocks." It is a function of VIX, a function of its own trend, a function of the state of stablecoins, and a function of institutional breakpoints.

I did not merely calculate simple correlations. I employed event studies, local projections, Chow structural breaks, Baron-Kenny mediation analysis, Granger causality, cointegration tests, state-dependent grouping, quantile regression, and cross-correlation functions; I did everything that needed to be done. The policy shock used is the daily change in the 2-year U.S. Treasury yield on FOMC days as a daily frequency proxy variable, not the high-frequency USMPD target/path factors. Therefore, it may contain non-pure policy components such as inflation expectations, term premiums, and information from press conferences. The FOMC statement is released at 14:00 Eastern Time, and BTC trades 24/7, making it impossible to strictly identify high-frequency immediate reactions after announcements using daily frequency data. There have only been 21 FOMC meetings since the ETF, resulting in low degrees of freedom for the subsample. I did not obtain daily flow data for the ETF and derivatives leverage. Mediation analysis can only indicate the direction of contemporaneous statistical relationships and cannot independently identify causal transmission chains. Cointegration does not imply causation; Granger leading does not equate to "seeing the future." These limitations must be stated upfront. Therefore, what this article aims to convey is not "I have proven what BTC has become," but rather that nine years of data tell us one thing: the past single-threaded BTC macro formula can no longer explain the current facts.

The real challenge has never been predicting whether the Federal Reserve will raise or lower interest rates next. The real challenge is determining how BTC will respond when the next macroeconomic shock arrives—will it be the last one in the parking lot to know the news, but the one that gets hit the hardest, or will it be the canary that might chirp early, or perhaps it will be an independent market buoyed by the expansion of stablecoins, completely indifferent to what the Federal Reserve is saying.

Understanding which of these it currently is, is far more useful than remembering the phrase "rates up, markets down; rates down, markets up."