does cryptocurrency follow the stock market? A guide

Do cryptocurrencies follow the stock market?

This article asks and answers the central question: does cryptocurrency follow the stock market? We examine whether major cryptocurrencies (notably Bitcoin and Ethereum) move in tandem with equity indices, why correlations change over time, what academic and industry studies find, and what practical implications follow for investors and traders. Readers will leave with clear definitions, empirical magnitudes, episode-based evidence (including 2020–2025 developments), measurement guidance, and conservative portfolio-level implications. Where implementation matters, Bitget products and Bitget Wallet are noted as practical options for custody and trading.

Definitions and key concepts

Correlation vs. causation

Correlation measures the statistical association between two time series (for example, daily returns of Bitcoin and the S&P 500). A common metric is the Pearson correlation coefficient, which ranges from −1 (perfect negative correlation) to +1 (perfect positive correlation). Practical studies often use rolling correlations—correlations computed over a moving window (e.g., 30, 60, or 120 trading days)—to see how association changes over time. Important: correlation does not imply causation. Two markets can move together because they share common drivers (macroeconomic shocks, sentiment) rather than one market directly causing moves in the other.

Risk-on / risk-off assets and beta

Market participants often describe assets as “risk-on” (assets that do well when investors are willing to take risk) or “risk-off” (assets that outperform when risk appetite falls). Cryptocurrencies have frequently behaved like high-beta risk assets—showing larger percent moves in the same direction as equities during rallies and selloffs. Beta here denotes sensitivity: a crypto asset with beta >1 versus an equity benchmark tends to amplify market moves, whereas beta <1 indicates lower sensitivity.

Common benchmarks and crypto proxies

Researchers and practitioners compare crypto to equity benchmarks such as the S&P 500 and Nasdaq-100. For crypto, typical proxies include Bitcoin price, Ethereum price, total crypto market capitalization, and institutional indices (for example, MVIS Digital Assets Index). Studies also use derivatives indicators—futures open interest and implied volatility—when examining cross-market dynamics.

Historical overview of the relationship

Early years (pre-2020)

In crypto’s early years, markets displayed low measured correlation to equities. Bitcoin and many altcoins were primarily retail-driven, thinly traded by comparison to large-cap stocks, and often moved on idiosyncratic news (protocol upgrades, hacks, ICO cycles). For much of the 2010s, commentators treated crypto as a distinct speculative asset class rather than an integrated part of global risk-asset portfolios.

2020 shift and increasing comovement

Two developments around 2020 changed that view. First, the March 2020 global risk-off event saw a near-synchronous plunge across many asset classes, including crypto; this episode revealed crypto’s vulnerability to broad liquidity shocks. Second, institutional participation began to grow—asset managers, custodial services, and later spot ETF structures increased institutional flows. From 2020 through 2022, many studies documented a rising positive correlation between major cryptocurrencies (especially Bitcoin) and equity indices, a trend tied to shared macro drivers and portfolio integration.

Episodes of decoupling

The relationship has not been monotonic. There have been several notable decoupling episodes driven by crypto-specific shocks—exchange failures, large protocol hacks, or concentrated deleveraging in crypto derivatives—that pushed crypto prices lower independent of stock-market performance. The late-2022 FTX collapse is an example: crypto markets suffered severe, idiosyncratic stress even as some equity sectors behaved differently.

Recent developments (2024–2025)

As of April–May 2025, industry reporting shows a mixed picture. As of April 4, 2025, Bloomberg reported signs that Bitcoin’s correlation with stocks had begun to break down in some periods, while other analyses (May 21, 2025 CME/OpenMarkets commentary) documented episodes where correlations remained elevated. Meanwhile, spot Bitcoin ETF approvals (2024–2025) and ongoing institutional adoption pushed some researchers to expect longer-term integration. At the same time, narratives about Bitcoin acting partly like a store-of-value (as suggested in ARK Invest commentary in 2025) introduced more heterogeneity in how investors treat crypto, contributing to varying correlation behavior across time.

Empirical evidence and studies

Rolling-correlation findings

Empirical work commonly computes rolling Pearson correlations on daily or weekly returns. Typical findings: correlations between Bitcoin and the S&P 500 were low (near zero) in much of the pre-2020 era, rose meaningfully from 2020–2022, and exhibit strong time variation. Correlations tend to spike during periods of market stress—when liquidity dries up and investors sell risk assets broadly. Conversely, correlation can fall during crypto-specific rallies or idiosyncratic drawdowns.

Representative studies and summaries

Major industry pieces and index providers (CME/OpenMarkets, WisdomTree, Bitstamp, Equiti, The Block, Investopedia) converge on two broad conclusions: (1) correlations between major cryptocurrencies and equities have increased since 2020, and (2) these correlations are not stable—regime shifts and event-driven dynamics matter. As of May 21, 2025, CME/OpenMarkets summarized that institutional exposure and macro-driven flows account for substantial shared variation. As of April 4, 2025, Bloomberg highlighted recent periods where the previously tight link has shown signs of weakening, underscoring the time-varying nature of the relationship.

Quantitative magnitudes

Reported correlation magnitudes depend on sample selection and methodology. A representative range often cited in industry summaries is: long-run average correlations near 0.1–0.3 during calmer periods, but spikes to 0.4–0.6 or higher during acute stress. These ranges are illustrative: daily-return correlations computed with short rolling windows tend to show larger variability, while monthly-window correlations are smoother but can lag regime shifts. Always check the window length and frequency when comparing reported figures.

Drivers of correlation (why crypto and stocks sometimes move together)

Institutional adoption and portfolio integration

As institutional investors gain exposure—via custody solutions, futures, ETFs, and balance-sheet holdings—crypto becomes a line item in diversified portfolios. When institutions rebalance or adjust overall risk exposure, trades can move both equities and crypto in the same direction. Spot ETF inflows since 2024–2025 are a concrete channel raising interdependence between crypto prices and broader financial flows.

Macroeconomic and monetary factors

Macro drivers—interest-rate expectations, liquidity provision by central banks, inflation surprises—affect discount rates and risk premia across many assets. A rate tightening cycle that lowers risk appetite can pressure both stocks and high-beta crypto assets. Conversely, a liquidity-rich environment can lift many risk assets simultaneously. These shared macro exposures explain a substantial portion of observed comovement.

Market structure and liquidity

Crypto markets operate 24/7 and rely on global liquidity providers and derivatives venues. While market hours and microstructure differ from equities, derivatives (futures and options) create tight linkages in risk management—liquidity-driven deleveraging in one market can transmit to the other through funding costs, margin calls, and cross-asset hedging strategies.

Behavioral channels and investor flows

Retail sentiment, social-media-driven trading, and simple portfolio flows (rebalancing between risk and safe assets) can cause synchronized moves. During market-wide fear episodes, investors often sell the most liquid or correlated risk positions first, producing parallel declines across stocks and crypto.

Asset-specific shocks

Crypto-specific shocks—protocol exploits, custody failures, or concentrated liquidations—can drive sharp crypto price moves that diverge from equities. Similarly, company-specific earnings shocks or sectoral news can move particular stocks independently of crypto, generating temporary divergence.

Asset-level differences and heterogeneity

Bitcoin versus altcoins

Bitcoin often behaves as the anchor of crypto markets and therefore shows stronger, more consistent correlation estimates with macro and equity markets than smaller altcoins. Altcoins can be driven by idiosyncratic narratives (DeFi, NFTs, gaming), lower liquidity, and supply events, producing more dispersion and intermittent decoupling from equities.

Stocks with crypto exposure

Certain equities—miners, blockchain-software firms, and publicly listed companies holding crypto on their balance sheet—have direct economic exposure to crypto prices and naturally show higher correlation with crypto than the broad market. When discussing trading or portfolio hedging, investors should separate broad equity indices from niche equity names that have explicit crypto links.

Safe-haven narratives vs. speculative narratives

Conflicting narratives coexist: some market participants see Bitcoin as “digital gold” (a store-of-value and hedge), while others treat it as a high-beta speculative asset. The prevalence of either narrative in investor behavior affects measured correlation with equities. For example, if Bitcoin increasingly functions as a store-of-value during a given period, its correlation to equities may fall.

Methodological issues and limitations

Choice of time frame and sampling frequency

Measured correlation is sensitive to whether analysts use intraday, daily, weekly, or monthly returns—and to the rolling-window length. Short windows capture fast-moving regime changes but can be noisy; long windows smooth noise but may obscure recent structural shifts. There is no single “correct” window—choose one aligned with your decision horizon.

Non-stationarity and regime shifts

Financial time series are non-stationary: the statistical relationship between crypto and equities can structurally change after major events (e.g., new regulatory regimes, large ETF launches, or market-structure changes). Non-stationarity limits the reliability of historical correlations for forecasting future comovement.

Data selection and survivorship bias

Index composition matters. Using different crypto baskets (top 10 by market cap vs. total market cap) or different equity benchmarks produces different correlation estimates. Studies that ignore delisted coins or short-lived tokens can suffer survivorship bias. Use full-sample, quality-controlled data when possible.

Statistical pitfalls

Watch for spurious correlations and multiple-testing issues. Correlation spikes in samples with extreme outliers can be driven by one-off events. Robust methods—Winsorizing returns, using rank correlations, or complementing Pearson correlations with copula or cointegration tests—help ensure more reliable inference.

Implications for investors and portfolio construction

Diversification and hedging

Because correlations vary, crypto may provide diversification benefits at times but act as another risky exposure at others. Investors seeking diversification should treat crypto allocations conservatively and stress-test portfolios for scenarios where crypto correlates strongly with equities. Simple mean-variance arguments alone are insufficient when correlation regimes switch.

Risk management and allocation sizing

Position sizing should account for crypto’s higher realized volatility and occasional correlation with equities. Practical risk steps include volatility scaling (reducing notional size when crypto volatility rises), setting concentration limits, and running scenario analyses that include joint equity-crypto drawdowns.

Trading strategies and tactical uses

Short-term traders can exploit changing cross-market signals—funding spreads, futures basis, and cross-market implied volatilities can inform tactical trades. Long-term allocators should define whether crypto serves as a return-seeking allocation or a thematic store-of-value, and build allocation rules accordingly. In all cases, avoid assuming a fixed correlation when constructing hedges.

Regulatory and custody considerations

Operational differences between equities and crypto—custody models, settlement mechanics, regulatory frameworks—affect how investors implement exposures. For custody and trading, consider regulated, institutional-grade providers. Bitget offers custody integrations and the Bitget Wallet for self-custody needs; investors should match custody choices to their regulatory environment and risk tolerance.

Case studies and notable episodes

March 2020 coronavirus crash

In March 2020 global risk-off conditions triggered a synchronized selloff across many assets. Bitcoin plunged alongside equities as liquidity needs forced rapid unwinds. This episode illustrated that crypto can lose diversification value in acute liquidity crises—correlations rose sharply during the dislocation.

2022 bear market and FTX collapse

During 2022’s broad crypto downturn and the late-2022 FTX collapse, crypto experienced severe stress that in parts was idiosyncratic to the industry. The FTX event, driven by industry-specific contagion, produced deeper crypto losses than contemporaneous equity moves in some periods—demonstrating that crypto can also decouple from equities when industry shocks dominate.

2024–2025 ETF era and recent correlation dynamics

As of mid-2025, the introduction and growth of spot Bitcoin ETFs and broader institutional access have been linked to increased cross-market integration. Yet, industry reporting in April–May 2025 shows mixed signals: while some analyses detect elevated comovement, others (including Bloomberg’s April 4, 2025 piece) report episodes where the correlation weakened. The coexistence of stronger institutional flows and distinct crypto narratives (e.g., digital-gold framing) explains this ambivalence.

How to monitor and measure correlation in practice

Tools and metrics

Common practical tools include rolling Pearson correlations (with multiple window lengths), rank correlations, cointegration tests (to check for long-run equilibrium relationships), copulas (for tail dependence), and volatility-adjusted correlations. For derivatives-focused monitoring, track futures open interest, funding rates, implied volatility, and cross-market basis spreads.

Data sources

Reliable data sources include institutional market-data providers (Bloomberg terminals, CME data) and reputable crypto data vendors (exchange APIs aggregated by index providers, CoinMarketCap-style aggregators, and professional index providers). When implementing, verify data completeness (24/7 crypto trading) and adjust timestamps to align markets across time zones. Bitget’s API and Bitget Wallet on-chain metrics can serve as practical inputs for traders using Bitget products.

Conclusions and open questions

Short answer to the framing question: does cryptocurrency follow the stock market? The best current assessment is nuanced. Since 2020, cryptocurrencies—particularly Bitcoin—have shown increased positive correlation with equities driven by institutional adoption and shared macro drivers. However, correlations are time-varying, regime-dependent, and subject to crypto-specific shocks that produce episodes of decoupling. Investors should not treat the relationship as stable or causal.

Open research and policy questions remain: Will continued ETF flows and deeper institutional participation permanently raise correlations? Can improved market-making and liquidity provisioning reduce correlation spikes during stress? How will regulatory frameworks introduced in 2024–2025 reshape cross-market dynamics? These unresolved issues mean practitioners must monitor metrics continuously rather than rely solely on historical averages.

References and further reading

Key reports and industry articles informing this guide include: Bloomberg ("Bitcoin’s Correlation With Stocks Shows Signs of Breaking Down", April 4, 2025), CME Group/OpenMarkets commentary ("Why Bitcoin's Relationship with Equities Has Changed", May 21, 2025), WisdomTree research on dynamic correlations, Bitstamp and Bitget market analyses (2024–2025), The Block ("Why is Bitcoin sometimes correlated to the stock market?", May 27, 2024), Investopedia primer on market correlation, Equiti and Phemex Academy pieces (2024–2025), and industry news summarizing ETF flows and ARK Invest commentary (2025). For readers seeking deeper academic study, search for peer-reviewed papers on time-varying correlations, copula-based tail dependence, and cointegration between crypto and traditional assets.

See also

• Market correlation
• Risk-on / risk-off
• Bitcoin ETFs
• Market microstructure
• Asset allocation

Notes on sources and data timing

As of April 4, 2025, Bloomberg reported shifting correlation patterns. As of May 21, 2025, CME/OpenMarkets published analysis on changing relationships between BTC and equities. Industry coverage and on-chain metrics cited in this article refer to data available through mid-2025; readers should verify the latest figures when making decisions. All data points cited are intended for informational and educational purposes, not investment advice.

Practical next steps

If you are monitoring cross-market risk exposures, start by computing multiple rolling correlations (short and long windows) between Bitcoin, Ethereum, and your chosen equity benchmarks; complement correlation analysis with volatility and futures-open-interest monitoring. For traders and investors looking for custody and trading infrastructure consistent with institutional standards, explore Bitget’s trading products and Bitget Wallet for custody and on-chain visibility. Consider building stress scenarios where correlations rise to 0.5–0.7 to understand portfolio impact under severe market dislocations.

Note: This article does not provide investment advice. It synthesizes industry reporting and research findings to explain the evolving statistical and economic relationship between cryptocurrencies and equity markets.