By Key Points
- TXMCtrades says global M2 tracking for Bitcoin is mathematically unsound
- Inconsistent data updates distort long-term crypto trend analysis
- China’s M2 behavior and FX effects skew the overall dataset
- Offset models used to sync M2 and Bitcoin are called arbitrary
A growing number of crypto analysts use Global M2 money supply data to predict Bitcoin’s price moves. But not everyone’s buying the hype.
I know many of you want to see the updated version of the BTC vs Global M2 chart. Here it is… just a very small part of the weekly Macro Investing Tool (MIT) as part of RV Plus.
It is time, give or take a few days… pic.twitter.com/dTF7RET5OL
— Raoul Pal (@RaoulGMI) April 16, 2025
Popular financial analyst TXMCtrades has sounded the alarm, saying these methods are flawed at their core. In a sharp post on X (formerly Twitter), he criticized the use of Global M2 to forecast Bitcoin, calling it “mathematically unsound” and “misleading.”
At the center of the debate is a chart from macro investor Raoul Pal that tracks Bitcoin’s price against Global M2. Many analysts interpret rising M2 as a bullish signal for BTC. After all, more money in the system could mean more capital flowing into risk assets like crypto.
But according to TXMCtrades, the way analysts are building and interpreting these charts is broken.
He notes that Global M2 data isn’t updated consistently—some countries provide weekly updates (like the U.S.), while others only report monthly or even less frequently. The result? Analysts are creating high-frequency charts from low-frequency data.
People, you can’t create a daily or weekly time series of “Global M2” when the United States is only updating M2 on a weekly basis and all others are monthly! You are looking at basically 30 out of 31 days of FX fluctuations with a static once-monthly global aggregate multiplied… pic.twitter.com/p5fpc4eTvs
— 𝐓𝐗𝐌𝐂 (@TXMCtrades) April 16, 2025
This, he explains, leads to over-representation of short-term volatility, especially movements caused by currency exchange rates, not real changes in money supply.
“You’re looking at an M2 weighted inverse dollar exchange rate 95% of the time,” he added. “Be better at math!”
China’s Role in Skewing the Global M2 Picture
Another red flag? China’s massive influence on Global M2 data. TXMCtrades pointed out that China alone accounts for 46% of the global M2 money supply in dollar terms. This alone can distort any trend analysis, especially since China’s M2 continues to climb, despite the country’s struggles to ease out of long-term debt deflation.
“China’s M2 goes straight up,” he said. Meanwhile, the U.S. M2 supply is still below its 2022 peak, and growing at the slowest pace since Bitcoin was born (excluding the post-COVID period from 2022 to 2024). That discrepancy alone throws off the idea of a unified global trend.
As governments across the world tighten or loosen monetary policy, inconsistent data inputs and FX fluctuations make the global M2 model increasingly unreliable for real-time or near-future Bitcoin predictions.
In fact, this echoes recent debates about market volatility itself, particularly as Bitcoin ETFs are quietly reducing price swings, making forecasting even trickier.
Are Time Lag Models Just Overfitted Guesswork?
Many analysts apply arbitrary time lags or offsets—like saying Bitcoin follows M2 with a 12-week delay—to try to fit historical patterns. Raoul Pal suggests a 12-week lag, while others like Colin Talks Crypto go with 15.4 weeks. Still others estimate between 10.7 and 15 weeks.
“Money is money, it doesn’t have a wait time,” TXMCtrades argued.
Some even stretch the concept further, applying these lags to altcoins like Solana (SOL). One analyst, Curb, claimed:
Solana
vs
Global M2 (+100 days)$SOL has been following Global M2 Money Supply (+100 days) its last 2 legs up.If this continues, $SOL is set to pump massively within the next 2 weeks.#SOLANA ⚡️ pic.twitter.com/cID4km9gM1
— curb (@CryptoCurb) April 15, 2025
But according to TXMCtrades, these lag models are overfitted—they might look good on past charts, but they don’t reliably predict future moves.
He argues these practices are closer to “scammy analysis” than serious financial modeling. His call to action? Bring more mathematical rigor into the crypto space and stop relying on visual tricks or historical curve-fitting.
This comes at a time when the crypto market is seeing a surge in complex narratives—from Coinbase facing backlash over memecoin listings to Ethereum dApps generating over $1B in Q1 fee revenue. In such a fast-evolving landscape, simplified and unproven models could do more harm than good.
What This Means for Crypto Forecasting and Retail Traders
TXMCtrades’ criticism isn’t just a technicality—it holds real implications for retail investors and the broader crypto industry. Many traders depend on macro models like Global M2 correlation charts to time entries or exits. If those models are flawed, they could lead to poor decisions based on misleading signals.
The analyst’s warning is especially relevant now, as retail interest grows following events like the Bybit PAWS airdrop frenzy and community-driven OM token burns. The need for solid, math-backed models is rising alongside hype and speculation.
In short, while it’s tempting to simplify Bitcoin’s future based on broad macro data, blindly trusting Global M2 models may be more harmful than helpful.
Analysts like TXMCtrades urge the industry to stop treating correlation as causation and focus on real economic signals and crypto-native fundamentals. If not, investors may find themselves chasing shadows in the data.
What's your reaction?
