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Factors/Liquidity/Relative Illiquidity
Aperiodic · AF-ILQ · FactsheetAs of Sep 14, 2026
AF-ILQ

Relative Illiquidity

relative_illiquidity

Captures the effect of assets with higher relative illiquidity tending to outperform.

CAGR
+15.26%
Ann. vol
14.5%
Sharpe
1.05

How the factor is constructed

The factor capitalizes on the persistent effect of higher relative illiquidity tending to outperform among mid/large-cap digital assets. Relative illiquidity is the arithmetic mean of half a dozen relative liquidity ratios — including volume, open interest, order-book depth and spread — usually denominated by market capitalization and aggregated across the top ten most reputable exchanges.

The universe consists of the most liquid and actively traded assets, identified on a rolling basis and survivorship-bias free. Positions are scaled by the inverse of rolling volatility; the factor is available point-in-time with hourly updates.

Signals
Liquidity Cross-sectional
Construction
Rank-weighted Long / short
Risk
Vol-targeted Inverse-vol scaled
Data
Point-in-time Reproducible

Relative Illiquidity

Jan 01, 2020 – Sep 14, 2026
76123169215261307Jan 20Feb 21Mar 22May 23Jun 24Aug 25Sep 26
Performance & risk by period
PeriodReturnBTCAnn. volSharpeMax DD
1 month-3.58%+24.10%——-4.9%
3 months-3.22%+17.86%——-4.9%
Year to date-4.33%-11.92%——-8.7%
1 year-6.63%-32.28%14.9%-0.33-11.8%
Since inception (CAGR)+15.26%+42.73%14.5%1.05-20.3%
Implementation paths · AF-ILQ

Putting Relative Illiquidity to work

There are two ways to take Relative Illiquidity from factsheet to live book: overlay it as a sleeve on the portfolio you already run, or use it as a building block in a standalone multi-factor portfolio. Both paths are documented in short, runnable notebooks that work out of the box against the public demo key — no signup required.

Notebook 01 · IPYNB

Add Relative Illiquidity to an existing portfolio

Size a Relative Illiquidity sleeve alongside your current book and quantify what it changes: correlation to your existing returns, then CAGR, volatility, Sharpe and maximum drawdown before and after the blend. One parameterized notebook runs for any factor — swap in Relative Illiquidity, then bring your own daily returns as a CSV or start from the built-in demo book.

Open the notebookDownload .ipynb
Blend impact · illustrativebefore → after
Your book+ AF-ILQ sleeve
Inputs
Your CSV · demo
Reports
Corr · Sharpe · DD
Notebook 02 · IPYNB

Build a portfolio from scratch

Construct a market-neutral multi-factor portfolio from the ground up: ensemble the raw signals, apply inverse-volatility weights with a per-asset cap, and backtest net of transaction costs. The default factor list reconstructs the 7 Factor Composite; add Relative Illiquidity to the factors list to measure its marginal contribution to the blend.

Open the notebookDownload .ipynb
Target weights · one daylong / short
BTC+19%
ETH+13%
SOL+8%
LINK+3%
AVAX-3%
XRP-8%
BNB-13%
DOGE-19%

New to the platform? The five-step guide covers data access, a proof of concept, and licensing.

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Factor properties
Ticker
AF-ILQ
API id
relative_illiquidity
Family
Liquidity
Universe
Top 40 Market Cap
Default smoothing
None
Rebalancing
Daily, hourly updates
History from
Jan 01, 2020
As of
Sep 14, 2026
Point-in-time
Yes — no look-ahead
Since inception (CAGR)
+15.26%
Max drawdown
-20.3%
Daily turnover
12.3%
Avg net exposure
10.9%
Avg gross exposure
93.4%
Downloads & links
PDFFactsheetCSVPortfolio returnsCSVRaw factor dataIPYNBAlphaLens notebookIPYNBIntegration notebook

Licence this factor

Custom pricing based on AUM, live weights via API, and methodology access under NDA.

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Aperiodic Factors

Institutional cross-sectional alpha factors for digital-asset desks — extracted from liquidity, flow and market microstructure metrics.

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Provided for informational purposes only; not investment advice, a recommendation, or an offer to transact. Past performance is not indicative of future results.

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