Factor Friday - May 22, 2026

Factor Friday: Market Pulls Back and Growth Outperforms

The week ending May 22 brought a sharp reset to the recovery narrative. The Market factor printed -5.65%, the worst single-week reading of the year and a full reversal of the +2.33% gain from the prior week. More notable than the drawdown itself was the factor leadership beneath it. Growth (+0.77%) and Value (+0.65%) were the only positive contributors, an unusual configuration in which fundamental quality outperformed during a broad selloff. Size held a small positive print at +0.39%, while Momentum (-0.15%) was nearly flat. The headline disappointment was Downside Beta, which fell -0.75% despite the drawdown, signaling that historically resilient assets did not provide the hedge investors typically expect. Over the trailing four weeks, Value (+3.78%) and Size (+2.30%) remain the strongest factors, with Market now at +0.13% as the May rally has been fully unwound. Year-to-date, Downside Beta still leads at +3.59% and Market has deepened to -23.16%. The takeaway for investors: the regime has shifted from beta-chasing recovery to a quality-driven, fundamentals-rewarding tape.

Rolling Factor Rankings and Rotation

The quilt chart shows a complete reordering of leadership. Growth moved from fourth last week to first this week, its highest rank in the periods shown. Value held a top-three position for the third consecutive week, demonstrating durable strength. Market collapsed from first to last in a single week, the sharpest rank reversal in the table. Downside Beta, which posted a strong +2.14% gain just last week, slipped to sixth, an important signal that the defensive trade is not behaving as expected during the current drawdown.

Month-to-date readings reinforce a fundamentals-led regime. Value leads at +3.62%, followed by Size at +2.53% and Market at +0.66%. Momentum is the clear MTD laggard at -4.86%, extending its multi-month weakness. The combination of strong Value and weak Momentum points to a market that is rotating into assets with visible fundamentals and away from recent winners. For investors, this argues for rebalancing toward fundamental factor sleeves and reducing reliance on trend-driven exposures.

Market and Key Factor Betas

Market Beta

The high market-beta cohort remains anchored by speculative and narrative-driven tokens: meme coins, gaming-adjacent assets, AI infrastructure, and L2 scaling plays. These names continue to move 1.5x or more with the broad market and were the primary victims of this week's drawdown. The low market-beta cohort is dominated by Bitcoin, large-cap proof-of-work assets, and select enterprise or regulatory-themed tokens. Composition is essentially unchanged week over week, which means the dispersion between high and low beta cohorts remains the dominant lever for portfolio construction in this environment.

Downside Beta

The high downside-beta cohort (assets least sensitive to drawdowns) remains concentrated in established Layer 1s, payment-oriented tokens, and policy or enterprise narratives. The roster is unchanged from last week, with only marginal beta shifts. The low downside-beta cohort (assets that amplify market declines) continues to be populated by higher-beta L2s, meme coins, and recent narrative tokens. Despite stable composition, the factor delivered a negative print during a -5.65% Market week, indicating that the resilient cohort did not outperform as it has historically.

Growth

The high growth-beta cohort is composed of tokens whose returns most closely track the long side of the growth long/short portfolio: WLFI leads, followed by DeFi infrastructure (LDO, MKR, OP), modular L1s and scaling layers (POL, ICP, XLM, LINK), and select narrative tokens (PENGU, WIF). These names move in tandem with the high-growth basket and benefit when the factor prints positive. The low growth-beta cohort tracks the short side of the construction: Bitcoin appears in the bottom 10, alongside JASMY, GALA, FET, WLD, STX, and BCH. Their returns move against the growth factor, meaning their return pattern aligns with low-growth assets in the model regardless of underlying network metrics. With the factor up +0.77% this week, the spread between the long and short cohorts is the source of factor return, not the absolute growth characteristics of any individual token.

What Factors are Driving Markets

Sectors

Total factor contributions summed to 3.47% against an index cumulative return of 5.31%, leaving a gap of approximately 1.8 percentage points. This is a dramatic narrowing from last week's reading near 15 percentage points and reflects both the reduction in index return (as the May rally faded) and continued positive factor contributions. Size remained the dominant contributor at +3.10%, with Growth (+1.25%), Momentum (+0.40%), and Value (+0.42%) all additive. Liquidity (-1.31%) and Downside Beta (-0.39%) detracted.

Services

Services factor contributions totaled 5.45% against a 3.54% index return, with factor contributions now exceeding the index by approximately 1.9 percentage points. This inversion is the first of its kind in the period and signals that systematic factor exposures more than account for the move in Services constituents. Size (+3.78%) and Growth (+1.55%) led contributions, with Value (+1.18%) also additive. Momentum (-0.64%) was the largest drag. For factor-aware investors, the Services category is now a textbook case of style exposure explaining the move.

Settlement

Settlement factor contributions netted to approximately -0.11% against an index return of -3.19%, leaving a gap of roughly 3.1 percentage points with the index more negative than factors would suggest. Notably, Settlement has now turned negative over the trailing 30 days, the first such reading in the data window. Size (-0.10%) was the largest drag, with Growth and Value also marginally negative. The category continues to show very low factor sensitivity overall, consistent with its BTC-heavy composition.

Taken together, the contribution picture has flipped meaningfully. Where May's rally was driven primarily by idiosyncratic asset performance, this week's drawdown is being driven more by systematic factor exposures, particularly Size and Growth on the upside, with broad cohort weakness on the downside. For investors, this means factor-aware portfolio construction is regaining its explanatory power, and rebalancing decisions based on factor exposures could make more sense in the near term.

Appendix: CF Factor Methodology

Market Factor

The market factor captures the broad, systematic risk that permeates the digital asset ecosystem. It reflects aggregate influences such as macroeconomic conditions, investor sentiment, and overall market volatility. As such, this factor is defined by the daily returns of the CF Broad Cap (Free Float Market Cap Weight) Index, offering a comprehensive and capitalization-weighted representation of the asset class.

Size Factor

The size factor captures the return differential associated with asset scale, reflecting the hypothesis that smaller-cap digital assets tend to outperform their larger-cap counterparts. This effect is understood to compensate for elevated operational and financial risks while exploiting potential market inefficiencies. In this framework, the size factor is defined by each asset’s fully diluted market capitalization. The value is sign-inverted so that higher z-scores are assigned to smaller assets and vice-versa.

Value Factor

The value factor reflects a protocol’s ability to generate economic output relative to its capital base and market valuation, combining measures of both efficiency and user engagement. It is constructed as the average z-score of two key ratios: transaction fees relative to total value locked (Fees/TVL) and daily active users relative to market capitalization (DAU/MCap). This composite metric captures how productively a protocol utilizes its resources while also serving as a proxy for user-driven demand. A higher combined score indicates efficient resource utilization and strong user engagement.

Momentum Factor

The momentum factor captures short-term price persistence by identifying assets that have recently exhibited strong performance. It is computed as the average z-score of two metrics: the 2 weeks cumulative performance and the 2 weeks risk-adjusted cumulative performance. This approach aligns with established findings in traditional financial literature and demonstrates empirical relevance in digital assets, where price trends tend to exhibit momentum over short horizons.

Growth Factor

The growth factor captures the expansion of a protocol’s network activity and user adoption. In the context of digital assets, it reflects metrics such as fee generation and user engagement, which serve as indicators of increased platform utilization and operational scale. The factor is defined as the average z-score of 30-day fee growth and 30-day weekly active user growth, thereby identifying assets exhibiting consistent and measurable increases in underlying network usage.

Downside Beta

The downside beta factor captures an asset’s sensitivity to adverse market conditions by isolating its behavior during periods of negative market returns. Empirical evidence shows that assets with lower downside beta tend to outperform their higher-beta counterparts over the long-term, due to their reduced participation in market drawdowns and more stable return profiles during periods of elevated volatility. As such, it is estimated through a regression of the asset’s daily returns over the most recent four-week period against market returns observed exclusively during negative sessions. The resulting value is sign-inverted to ensure that assets with lower downside exposure are assigned higher z-scores.

Liquidity Factor

The liquidity factor captures the ease with which a digital asset can be traded without significantly impacting its price. Empirical evidence shows that illiquid assets tend to command a higher risk premium than their more liquid counterparts, serving as compensation for trading friction and price volatility. To quantify this, the factor is measured using token turnover, defined as trading volume as a percentage of circulating supply. The value is sign-inverted such that higher z-scores are assigned to less liquid assets.

For further detail, view the CF Factors Methodology Document, the CF Factor Data Suite, and Our paper “A Factor Model for Digital Assets” in Springer Nature’s Mathematical Research for Blockchain Economy