Bitcoin Correlations

Five lines, five macro stories. Each is Bitcoin’s rolling 90-day Pearson correlation with a single reference market: GLD for the digital-gold thesis, TLT for long-duration / safe-haven flows, SPY and QQQ for broad-market and tech-beta risk, and IWM for small-cap risk. The linear right axis spans −1.00 to +1.00 with dashed reference lines at ±0.5 and a solid zero baseline. There is no price overlay — the chart is dense enough with five correlation lanes.

Today’s strongest correlate is IWM at +0.96; the gold reading is +0.17, the Nasdaq reading is +0.96. The regime classifier — defined in the next section — reads Risk-on linked. The series stretches from 15 Sept 2010 to the most recent close on 30 Apr 2026.

For each daily close t and each reference market X, the rolling 90-day Pearson correlation is:

ρ90d(BTC, X)t = Cov(rBTC, rX) / (σBTC · σX)

where r denotes daily log returns (ln(close / close−1)), and the covariance and standard deviations are computed over the trailing 90 aligned trading days. Equity returns are New-York-close-to-New-York-close; Bitcoin’s 24/7 returns are folded onto the equity calendar so the Friday-to-Monday bar carries the weekend price action. The 90-day window is the conventional choice — shorter windows whip on every macro surprise, longer windows lag too much to catch regime turns.

The five reference markets are exchange-traded funds rather than the underlying indices: GLD (SPDR Gold Shares), IWM (iShares Russell 2000), QQQ (Invesco QQQ Trust), SPY (SPDR S&P 500), and TLT (iShares 20+ Year Treasury Bond). ETFs are used so the dividend-and-distribution-adjusted total-return matches what an investable benchmark would actually deliver. The reconstruction matches mainstream research-desk practice; full derivation lives on the methodology page.

The regime label on the reading row is deterministic from the per-asset coefficients. If the strongest correlate by absolute value is below 0.30, the regime reads Idiosyncratic — Bitcoin is moving on its own. Above that threshold the label follows the top correlate: a high TLT coefficient prints Risk-off linked; GLD prints Gold-linked; SPY, QQQ, or IWM print Risk-on linked; a positive-but-flipping top correlate lands in Mixed.

Reading every cycle anchor against the live series surfaces how unstable Bitcoin’s correlation profile is. The 2017 cycle top printed close to the idiosyncratic baseline against every reference asset; by 2022, the network was coupled to the Nasdaq at coefficients above +0.6 for months. The 2024 pre-halving window saw gold and equities both elevated. Prices are our own daily closes; coefficients are pulled from the rolling-90-day series at the named date or the most recent prior close.

The single observation most competitor pages omit: Bitcoin’s gold correlation and Nasdaq correlation cross repeatedly. Each crossover is a regime flip from “digital gold” to “tech beta” or back. The table below walks the full daily-close history and emits a row for every regime that lasted at least thirty days. Gold-led regimes are the rarer of the two: across 5,707 trading days, Bitcoin spent 984 of them — 17.2% — with its 90-day GLD coefficient above its 90-day QQQ coefficient.

Three observations carry through every crossover regime on the table. First, the “digital gold” thesis is genuinely visible — just intermittently. Gold-led runs show up around banking stress, dollar weakness, and the months around the January 2024 spot-ETF launch. Larry Fink described Bitcoin in October 2024 as “an alternative to other commodities like gold”; the data places that statement inside a real but bounded regime, not a permanent reclassification.

Second, Nasdaq-led runs dominate the time-in-regime budget — especially since mid-2020. The Covid-era liquidity flush, the 2022 Fed hiking cycle, and the 2024–25 AI-led rally all produced multi-month windows where the QQQ coefficient sat above +0.5 and the GLD coefficient was a sideshow. Lyn Alden’s 2024 essay on Bitcoin as a global liquidity barometer argues the deeper driver is global money-supply growth: tech equities and Bitcoin both depend on cheap discount rates, and the equity-correlation is downstream of that shared sensitivity rather than the cause.

Third, the framing flips faster than narrative allows. Arthur Hayes frames Bitcoin as a global-fiat-liquidity barometer; the canonical institutional research note Bitcoin First positions it as an uncorrelated portfolio diversifier; Peter Schiff has argued Bitcoin is “negatively correlated” with gold in his debates with Saifedean Ammous. Each framing is a window in this data, not a constant. Today’s GLD reading of +0.17 and QQQ reading of +0.96 place the network in a Nasdaq-led regime; the next regime change will arrive on its own schedule.

An institutional research note on the factors driving gold and Bitcoin documents the long-run baseline plainly: across the post-2015 record, the 90-day BTC–GLD correlation has averaged about +0.10, with a peak of +0.57 and a trough of −0.37. The digital-gold thesis is a regime that fires, not a structural state.

For a portfolio allocator. Treat the digital-gold and tech-beta framings as regime-dependent rather than structural. Today’s coefficients say something about today’s portfolio diversification properties; nothing in the crossover record argues they will hold through the next macro regime change. Position-sizing on a permanent +0.5 Nasdaq correlation, or on a permanent zero, will both be wrong inside two years.

For a macro trader. The crossover table is the cleanest catalogue of Bitcoin’s regime-shift cadence on this site. Pair it with global M2 correlation for the liquidity lens, with Bitcoin dominance for the cryptoasset-internal share, and with spot ETF flows for the institutional-flow lens. Crossovers from gold-led to Nasdaq-led inside a thirty-day window have historically marked the start of a wider risk-on impulse; the reverse direction has marked dollar-stress windows.

For a researcher. Every coefficient on this page is reproducible from daily log returns on the underlying ETF and BTC daily-close series. The crossover detection is a thirty-day-minimum run-length filter on the GLD-vs-QQQ sign; the implementation is documented on the methodology page.

Pearson correlation is symmetric and direction-blind. A high BTC–QQQ reading tells you the two co-moved; whether tech dragged Bitcoin or Bitcoin dragged tech is a question this coefficient cannot answer. For causality, the appropriate tool is a Granger-causality test or a vector autoregression, not rolling Pearson; the coefficient sets the bound, not the direction.

Rolling-window correlations capture distribution overlap, not tail coupling. The 2020 Covid liquidity flush is the canonical case: Bitcoin and equities both fell sharply in March 2020 in a two-week window, but the 90-day coefficient barely moved because the bulk of the trailing window was pre-shock. Tail-event coupling needs a shorter window or an explicit drawdown overlay; the rolling Pearson smooths through it.

The reference universe is selective. The five ETFs cover gold, US equities (broad, tech, small-cap), and long bonds. They do not cover the dollar index, oil, EM equities, the yen carry, or credit spreads — each of which has a real claim on Bitcoin’s correlation surface in specific regimes. Add an asset and you may find a higher coefficient than anything on this page; the absence is not a denial.

Calendar-alignment loses weekend information. Bitcoin trades 24/7; equity ETFs do not. Folding the 24/7 returns onto Monday-to-Friday closes parks weekend price action inside the Friday-to-Monday bar. Major weekend moves (October 2023 Hamas attack, March 2023 USDC depeg) hit the chart as a single elevated Monday return rather than three separate prints. The coefficient absorbs this; the narrative attribution does not.

Canonical questions from Google’s “People also ask” block for bitcoin correlation gold and bitcoin nasdaq correlation, answered against the data on this page.