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⟁⊿⋔Returns, factors, and adoption · predictive
Do market, size, and momentum factors organize cryptocurrency returns?
Liu, Tsyvinski, and Wu report that cryptocurrency market, size, and momentum factors capture cross-sectional expected returns in their study universe.
Conditional
Liu, Tsyvinski, and Wu report that cryptocurrency market, size, and momentum factors capture cross-sectional expected returns in their study universe.
The peer-reviewed result is source-verified, but investability depends on universe construction, delistings, weighting, turnover, and costs.
Literature record
ConditionalWhat the reviewed source and linked counterevidence support.
Bathymark reproduction
Not startedThe investable-universe and execution specification remain open.
Live validity
Not monitoredSignal Lab is a current evidence surface, not this paper's factor portfolio.
where the claim applies
Scope and horizon
Assets
The paper's broad cross-section of cryptocurrencies
Venues or data
Paper-specific aggregated market data
Geography
Global crypto markets
Sample
The historical sample defined in the source paper
Horizon
Cross-sectional portfolio return horizons defined in the paper
source result
What the work reported
The paper reports that ten characteristic strategies are accounted for by its cryptocurrency three-factor model.
structured numbers
Characteristic strategies reported10 strategies
how the result was made
Method and implementation boundary
Design
Characteristic-sorted long-short portfolios and a cryptocurrency three-factor model.
Measures
Market return, market capitalization, momentum, and ten paper-defined characteristics.
Reality gap
No Bathymark reconstruction yet includes point-in-time listings, delistings, borrow, turnover, fees, or venue capacity.
Assumptions
The historical asset universe is free of survivorship and look-ahead bias.
The long and short legs were available at the stated portfolio formation times.
Limits
Factor explanation is not the same as an implementable strategy.
Small-token results can be dominated by thin markets, stale prices, and unavailable shorting.
A factor model can fit one sample and decay after publication.
Required reality checks
Use a point-in-time investable universe with delistings preserved.
Report equal-weighted and liquidity-aware results separately.
Apply cost, capacity, multiple-testing, and post-publication checks.
What this cannot mean
That small tokens should outperform now.
That a high backtest return is available to a real trader.
That every crypto characteristic is an independent source of return.
source and version trail
The works behind this record
Bathymark stores curated bibliographic facts and its own paraphrase. It does not store the source abstract or full text. Open the original work to inspect the complete analysis.
A factor portfolio result needs multiple-testing and non-normal-return controls before performance claims.
append-only assessment memory
Status history
ConditionalPrimary journal claim verified; implementability and post-publication validity remain untested.
current Bathymark context
Related live evidence, not a replication
Signal Lab is a current evidence surface, not this paper's factor portfolio.
Reviewed 2026-07-13; next review 2026-10-13. The paper record is not a recommendation, forecast, or proof of current profitability. Information, not financial advice.