2015issue C0556
Filter unexecutable futures by liquidity, open interest, and margin
A historical execution screen ranks listed futures by how readily size can be bought or sold, multiplies an equal-dollar contract count by open interest, and reads posted margin against the three-year dollar range so implementation cost is judged from dollars at risk.
- A liquidity filter ranks futures by activity intensity, historical range, and volume so thin books are rejected before an order is placed.
- Open-interest analysis multiplies an equal-dollar contract count by outstanding open interest so the book, not recent prints, decides whether the ticket is absorbable.
- Posted percent margin and effective percent margin must be read together, because face margin can understate implementation cost.
- Contracts with one activity mark or none are treated as harder to enter and exit and less suitable for speculative tickets.
A pre-trade screen for listed futures
A futures liquidity filter can rank contracts by combining point value, the largest three-year price excursion, open interest, and a volume adjustment, then scoring activity so thicker books sit above thinner ones. The screen ranks how readily size can be bought or sold and rejects thin markets before an order is placed.
Rank contracts by how readily size trades
The liquidity filter uses activity intensity, historical range, and volume so thin markets are rejected before an order is placed. Contracts with one activity mark or none are treated as harder to enter and exit and therefore less suitable for speculative tickets.
Put every listed market on one dollar scale
The equal-dollar contract count is tick dollar value multiplied by the three-year maximum price excursion. That step places every listed market on one potential-dollar scale before liquidity is compared, so ranks are not distorted by contract size.
Let open interest decide whether the ticket fits
Relative contract liquidity is that equal-dollar contract count times total open interest times a volume factor, so open-interest analysis sits at the center of the execution rank. The sizing check multiplies the equal-dollar contract count by outstanding open interest so the book, not just recent prints, decides whether the ticket is absorbable.
Adjust the rank for trading activity
The volume factor is the greater of 1 and the exponential of the natural log of volume divided by the natural log of 5,000, minus 2. The scalar lifts busy markets and penalizes quiet ones against a 5,000-contract baseline.
Read posted margin against the three-year range
Posted percent margin and effective percent margin must be read together. Effective percent margin is margin dollars divided by the three-year dollar range of the contract, then scaled to a percentage. Commission analysis compares face margin against that range-adjusted figure so implementation cost is judged from dollars at risk, not the posted percentage alone.
Face margin can understate implementation cost. Eurodollar, two-year notes, and 30-day fed funds showed 0.1, 0.1, and 0 percent posted margin but 81.9, 26.7, and 85.6 percent effective margin, and needed 507, 183, and 873 contracts on the equal-dollar scale.
Compare rows, not isolated figures
Figures in any one comparison column are proportional and only meaningful against other rows in that column, because every contract is already scaled to a common dollar-profit unit.
An equity analog for activity
Equity trading activity can serve as a liquidity proxy when period volume is expressed as a percentage of shares outstanding. That share-turnover rate is the turnover of the float.
Posted margin versus effective margin across listed futures

Effective percent margin is posted margin in dollars divided by the contract’s three-year dollar range, then times 100. Rows keep the source order from most to least liquid.
All readings on this track · 32 readings
- 1985Matching ticket size to negotiable commission schedules
- 1985Minimum tickets can price a small book out of its own exit
- 1992Stop-order slippage as an execution cost filter
- 1993Cost-aware walk-forward evaluation of pattern-detector signals
- 2001Audit high-turnover operating conditions as one procedure
- 2002Front-load futures commission and slippage
- 2005Inactive account fees as hidden implementation cost
- 2010A pre-trade liquidity screen for futures contracts
- 2011Currency option venues, spreads, clearing, and premium cost
- 2012Filter futures contracts by liquidity and implementation cost
- 2012Futures commission versus one tick of cost
- 2012Ranking futures liquidity for executable orders
- 2013Filter option day trades by spread, volume, and fees
- 2013Filter futures by liquidity, open interest, and effective margin
- 2014Book futures data fees as implementation cost
- 2015Use a futures liquidity rank as a pre-trade checklist
- 2015Filter unexecutable futures by liquidity, open interest, and margin
- 2015Futures liquidity ranking as an execution filter
- 2015Filtering option trades by bid-ask width
- 2016Exchange quote fees as execution costs and liquidity filters
- 2016Filter futures by liquidity, open interest, and margin cost
- 2016Comparing dollar-index futures execution costs and liquidity
- 2016A futures liquidity ranking as a screen for executable orders
- 2017Filter a futures board by liquidity, open interest, and implementation cost
- 2017Filter futures contracts by liquidity and margin cost
- 2017How residency rules raise futures implementation costs
- 2018Screen listed futures by liquidity, open interest, and margin
- 2018Contract selection is the first filter on competing bitcoin futures
- 2018Filter futures execution by liquidity and margin
- 2018Commission analysis for brokerage execution costs
- 2019Ranking futures liquidity before you size the order
- 2020Brokerage selection as an implementation-cost problem