CF Factor Data Series
- About
CF Factor Data Series provide a systematic framework for understanding the drivers of return and risk in digital asset markets. Built using a robust, rules-based methodology, these factors provide a toolkit to enable performance attribution, portfolio construction, and thematic screening across a range of style factors. Whether used by asset managers, researchers, or allocators, CF Factors offer transparency into market behavior and help bridge traditional finance practices with digital asset investing.
- Documentation
Factor Returns
Factor returns represent the performance of investment strategies designed to isolate specific, systematic sources of risk and return across digital assets. To achieve this, long-short portfolios are constructed by ranking assets according to the characteristics relevant to each factor. Factor returns aim to capture the component of performance attributable to a given factor, independent of market-wide movements.
SizeMeasures risk premium associated with market capitalization. Smaller-cap digital assets tend to outperform their larger counterparts, reflecting a risk premium that compensates for their higher operational and financial uncertainty.
ValueCaptures how efficiently a protocol generates activity and revenue relative to its size. Based on transaction fees, daily active users, total value locked and market capitalisation metrics, it reflects economic utility and user engagement. Assets exhibiting higher fee or usage intensity relative to their size are considered undervalued and, on average, tend to outperform lower-value counterparts.
MomentumMeasures recent price trends to capture short-term strength. Assets that have exhibited strong recent performance tend to continue outperforming over near-term horizons, while weaker-performing assets generally lag, consistent with established momentum effects observed in financial markets.
GrowthIdentifies assets with accelerating network activity and adoption. It is measured through the growth rates of transaction fees and daily active users. Assets demonstrating stronger user and revenue expansion tend to deliver superior returns relative to peers with slower growth trajectories.
Downside BetaQuantifies an asset's sensitivity to negative market movements. Assets with lower downside beta exhibit reduced responsiveness during market drawdowns and are expected to outperform its counterparts over time, particularly in volatile or risk-averse environments.
LiquidityAssesses the ease with which an asset can be traded without significantly impacting its price. It is proxied by token turnover relative to circulating supply. Less liquid assets are typically associated with higher transaction costs and greater price impact, but may offer higher expected returns as compensation for bearing liquidity risk.
Factor Scores
Factor scores are standardized indicators that reflect how strongly an individual asset expresses the characteristics of a given factor. They are derived from quantitative descriptors relevant to each factor — such as market capitalization for size, users and fee expansion for growth, or fee generation for value. These scores are employed to systematically rank assets across the investable universe, facilitating the construction of the relevant long-short portfolios.
Factor Exposures
Factor exposures represent the sensitivity of an asset's returns to the systematic risk captured by each factor. These are calculated as the beta coefficients from a rolling regression of an asset's daily returns against the daily factor returns for the market, size, value, momentum, growth, liquidity, and downside beta factors. A 3-year rolling window is used to estimate these exposures, enabling investors to assess how much an asset's price movement is explained by each underlying risk premium.
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