Over the past six years, we have systematically examined Bitcoin’s price behavior in relation to a wide range of macro‑economic indicators, with a particular focus on the U.S. Non‑Farm Payrolls (NFP) report.
The NFP, released each month by the Bureau of Labor Statistics, is one of the most closely watched pieces of economic data because it provides a snapshot of employment growth and is often interpreted as a proxy for the health of the broader economy. Traders in traditional markets frequently react strongly to the surprise component of the report—whether the actual number of jobs added exceeds or falls short of analysts’ expectations—by adjusting positions in equities, bonds, and currencies.
Given Bitcoin’s growing reputation as a digital store of value and, increasingly, as a speculative asset, it is natural to wonder whether the same kind of price volatility that accompanies a surprising NFP release also manifests in the cryptocurrency market. To answer that question, we compiled a comprehensive dataset that spans from early 2020 through the end of 2025, covering every monthly NFP release within that period.
For each release, we recorded the actual payroll number, the consensus forecast published by major financial institutions, and the absolute surprise (the difference between actual and forecast). In parallel, we captured Bitcoin’s closing price on the day of the release, as well as its price at several key intervals after the report—30 minutes, 1 hour, 4 hours, 24 hours, and 7 days later. This granular approach allowed us to isolate short‑term price reactions from longer‑term trends that could be driven by unrelated factors such as regulatory news, technological upgrades, or broader market sentiment.
Our statistical analysis began with simple correlation tests. The Pearson correlation coefficient between the magnitude of the NFP surprise and Bitcoin’s immediate price change (measured over the first hour after the release) hovered around 0.03, a value that is essentially zero and far below any threshold that would suggest a meaningful relationship. Even when we broadened the window to a full 24‑hour period, the correlation only rose to 0.07, still indicating a negligible connection.
To ensure robustness, we also performed non‑parametric Spearman rank‑order tests, which similarly returned values close to zero, confirming that the lack of association was not an artifact of outliers or non‑linear dynamics. Beyond correlation, we applied event‑study methodology commonly used in finance to assess abnormal returns surrounding a specific event.
For each NFP release, we calculated the expected Bitcoin return based on a market model that incorporates overall crypto‑market movements and the performance of a basket of major assets (such as the S&P 500, the U.S. dollar index, and gold).
The abnormal return—actual return minus expected return—was then averaged across all 72 NFP events in our sample. The resulting average abnormal return for the 30‑minute window was a modest +0.12%, with a standard error that rendered the figure statistically insignificant at the 95% confidence level. In other words, any price movement that did occur was indistinguishable from random noise. One might argue that the impact of the NFP could be conditional on broader market conditions.
To explore this, we segmented the data into periods of high volatility (defined as days when the Bitcoin volatility index, BVOL, exceeded its 75th percentile) and low volatility. In high‑volatility regimes, the average abnormal return modestly increased to +0.25%, yet the confidence intervals remained wide, and the result still failed to achieve statistical significance. During tranquil market phases, the abnormal return was essentially zero.
This pattern suggests that even when traders are more sensitive to news, the NFP report does not exert a systematic influence on Bitcoin’s price. We also examined whether the direction of the surprise—positive versus negative—had any asymmetric effect.
By grouping the events into “positive surprise” (actual > forecast) and “negative surprise” (actual < forecast) categories, we observed a slight tendency for Bitcoin to rise modestly after positive surprises (+0.15% on average) and to dip after negative surprises (‑0.10%). However, these differences were again within the margin of error and could be attributed to random fluctuations rather than a causal link. Why, then, does the NFP appear to be a muted driver for Bitcoin? Several plausible explanations emerge.
First, Bitcoin’s market participants are often more attuned to crypto‑specific catalysts—such as protocol upgrades, exchange listings, or regulatory announcements—than to macro‑economic data that primarily affect fiat‑based assets. Second, the global nature of the cryptocurrency market dilutes the impact of any single country’s employment figures; investors from Asia, Europe, and Latin America may place less weight on U.S. payroll numbers when making trading decisions.
Third, the increasing institutional adoption of Bitcoin has introduced a new class of investors whose risk‑management frameworks rely on diversified portfolios and longer‑term horizons, reducing the propensity to react impulsively to short‑term economic releases. It is also worth noting that while the NFP itself does not move Bitcoin prices dramatically, the broader macro‑economic environment that the NFP reflects can indirectly shape market sentiment. For instance, a series of strong payroll reports may signal a tightening monetary policy stance from the Federal Reserve, which could eventually affect interest rates, inflation expectations, and ultimately the attractiveness of risk‑on assets like Bitcoin.
However, such indirect pathways unfold over weeks or months, far beyond the immediate reaction window we studied. In conclusion, our six‑year empirical investigation demonstrates that the U.S. Non‑Farm Payroll report is not a significant short‑term price driver for Bitcoin.
The data show virtually no correlation, no statistically meaningful abnormal returns, and no consistent pattern of price movement tied to the direction or magnitude of the payroll surprise. Traders and analysts should therefore treat the NFP as a background macro‑economic indicator rather than a catalyst for Bitcoin’s price swings. Instead, focus should remain on cryptocurrency‑specific developments, broader market liquidity conditions, and the evolving regulatory landscape when seeking to anticipate Bitcoin’s next moves.