Why the analogy is useful
Cross-sectional factor investing rests on a small number of empirical regularities that have persisted across decades, geographies and asset classes: assets with higher recent returns tend to continue outperforming over short horizons, assets priced cheaply relative to fundamentals tend to outperform over long horizons, assets with stronger balance sheets and higher-quality cash flows tend to deliver better risk-adjusted returns, and positions that earn income while held often add to total return even when price appreciation is modest. The underlying thesis is that markets are efficient enough to punish naive mistakes, but inefficient enough that disciplined, systematic exposure to persistent return drivers pays off over full cycles.
Digital asset markets meet the first condition — they are efficient enough, in the liquid part of the universe, to punish naive mistakes — and the second — there is enough structural dispersion across assets and venues to reward disciplined cross-sectional construction. This is the reason factor thinking travels.
Where the analogy breaks
It travels with important caveats.
- Fundamentals are young. The equity "value" factor leans on decades of accounting data and a well-understood concept of intrinsic value. Digital assets have neither the history nor an agreed-upon concept of fundamental value. On-chain metrics — active addresses, fees, revenue, tokenholder flows — are useful but noisy, and their economic interpretation evolves faster than the literature can keep up.
- Carry is regime-dependent. In equities and currencies, carry is a first-order driver with reasonable persistence. In digital asset markets, the yield surface available to institutional participants changes materially with the macro cycle and venue structure. A carry model that does not adapt to regime is a carry model that will eventually blow up.
- Quality is hard to define. The equity-style "quality" factor aggregates profitability, leverage, and stability. The digital asset analogue has to be assembled from uneven data — developer activity, protocol revenue, governance concentration, custodial resilience — each with its own measurement error. The composite is real, but it is not a one-line formula.
- Momentum is fast. Cross-sectional momentum in digital assets operates on materially shorter horizons than in equities. Classical twelve-minus-one construction is, in this market, almost an anti-signal over long horizons. Shorter, regime-aware windows are more defensible, at the cost of higher turnover.
- Capacity is finite. Tokens have narrower borrow availability, shallower order books outside the top of the universe, and greater venue fragmentation than a typical equity universe. Capacity must be an input to the factor, not an afterthought.
How we approach it
The research engine behind our market-neutral book combines a small number of well-specified factors — momentum, carry, dispersion, liquidity, quality — inside a portfolio-construction layer that is explicit about capacity and turnover, with a neutralisation step that strips sector and market-beta exposure. Every factor is specified ex ante, validated out-of-sample, and stress-tested across historical regimes before it earns capital. Factors that fail out-of-sample do not get a second pass — we move on.
We also maintain a clear separation between what we consider durable edges — cross-sectional dispersion, microstructural mispricings, and certain classes of flow-driven effects — and narrative-driven signals, which we treat as research hypotheses rather than strategy components. Narrative is a context layer, not an alpha source.
What it means for allocators
For professional investors, the practical implication is that a systematic digital asset strategy should be evaluable with the same rigour as a traditional factor strategy:
- Does the strategy have an articulable thesis per factor, or does it rely on an opaque composite?
- Are factors validated out-of-sample, or are they anchored in a visually attractive back-test?
- Is the portfolio-construction layer explicit about capacity, turnover, and cost, or are costs treated as a back-test detail?
- Is the neutralisation step defensible — does the manager know, at any point, what exposures the book is and is not taking?
A credible answer to each of those questions is not sufficient to guarantee returns, but it is necessary to be investable.
Talk to our research team.
We are happy to walk professional investors through our factor stack, validation discipline, and portfolio construction in detail.