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2015issue C0756

Futures liquidity ranking as an execution filter

A historical futures table ranks how readily a listing can be bought or sold. Editorial reading: use it as a liquidityFilter first, then compare contractsToTrade and effectivePercentMargin on a shared three-year dollar range instead of treating notional size as a forecast.

  • A liquidityFilter starts with activity marks and sets aside listings with one mark or none, which the archive treats as little activity.
  • contractsToTrade and the equal-dollar column scale each futures listing to the same three-year dollar price range.
  • relativeContractLiquidity multiplies contractsToTrade by openInterest and a volumeFactor. Each column is meaningful only against other values in that column.
  • effectivePercentMargin expresses posted margin against the three-year dollar range, while shareTurnover is the equity analogue of trading liquidity.
Entries in this reading3 entries
Current trackCommission analysis37 readingsLiquidity filter118 readingsOpen interest analysis118 readings

A table for screening, not forecasting

The archive forms a futures liquidity ranking so that one listing can be compared with another on how readily the whole contract can be bought or sold. That score is relativeContractLiquidity. It combines a size-adjusted contract count, openInterest, and a volume adjustment.

Editorial reading: use the finished table as a pre-trade execution screen. First drop contracts that cannot be entered or exited cleanly. Then compare implementation cost with equal-dollar contract counts and effectivePercentMargin. Do not treat notional size as a forecast.

How the ranking is built

A futures liquidity ranking can be formed by multiplying contract point value by a three-year maximum price move, then by openInterest, then by a volumeFactor usually between 1 and 4.

The same ranking can be written as relativeContractLiquidity. It equals the contractsToTrade count times total openInterest times a volumeFactor defined as the greater of 1 or exp(ln volume / ln 5000) minus 2. The volumeFactor takes the greater of 1 and an exponential transform of volume versus a 5000-contract reference, and is applied when volume is unusually low or high.

The contractsToTrade figure equals tick dollar value times the three-year maximum price excursion. It is the number of contracts required so that each listed market is scaled to the same three-year dollar price range.

Contracts to trade for equal dollar profit, March 2020 listing

Each bar is how many contracts of that future had to be traded to match the same three-year dollar profit potential as the rest of the listing. Mexican peso and eurodollar sit at the high end (57 and 52 contracts); palladium, soybean meal, and Nasdaq 100 e-mini sit at one or two. Figures come from the Contracts to Trade for Equal Dollar Profit column of the March 2020 Trading Liquidity: Futures table, left to right in the source relative-liquidity order.
Each bar is how many contracts of that future had to be traded to match the same three-year dollar profit potential as the rest of the listing. Mexican peso and eurodollar sit at the high end (57 and 52 contracts); palladium, soybean meal, and Nasdaq 100 e-mini sit at one or two. Figures come from the Contracts to Trade for Equal Dollar Profit column of the March 2020 Trading Liquidity: Futures table, left to right in the source relative-liquidity order.Listed commodity and financial futures · March 2020

The source scales every listing as tick dollar value times the three-year maximum price excursion, so the bars share one dollar scale. Row order is relative contract liquidity (open interest times a volume factor), not bar height.

Activity marks as a first filter

Relative ease of trading is shown as a descending row of activity marks. Listings with one mark or none indicate little activity. A liquidityFilter prefers thicker activity marks and sets aside listings with little or no activity.

Equal-dollar scaling

An equal-dollar column rescales each futures listing by multiplying contract value by the largest price change observed over the prior three years, so every figure in that column represents the same dollar amount.

Editorial reading: once thin listings are set aside, this equal-dollar count is the place to compare how much size must be transacted, not a prediction of price.

Margin compared to the price range

effectivePercentMargin is margin in dollars divided by the three-year dollar price range of the contract, then multiplied by 100. It is posted margin expressed as a percentage of that three-year dollar price range. percentMargin is posted margin as a percentage of contract value and is used to compare capital lock-up across listings.

Editorial reading: these margin columns compare implementation cost and capital lock-up after the liquidityFilter, not a forecast of return.

Columns stay inside themselves

Each column is a proportional comparison and is meaningful only against other values in the same column.

A share turnover proxy for equities

For equities, period volume as a percentage of shares outstanding is presented as a turnover-rate proxy for trading liquidity. That proxy is shareTurnover: equity volume over a period divided by shares outstanding.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
18 of 32 in the Commission analysis track
201526-27 pp.Next on Commission analysisFiltering option trades by bid-ask widthThe displayed bid-ask spread is treated as an immediate transacting cost. A newly purchased long must recover that implementation cost, before commissions, before the position can show a gain.
All readings on this track · 32 readings
  1. 1985Matching ticket size to negotiable commission schedules
  2. 1985Minimum tickets can price a small book out of its own exit
  3. 1992Stop-order slippage as an execution cost filter
  4. 1993Cost-aware walk-forward evaluation of pattern-detector signals
  5. 2001Audit high-turnover operating conditions as one procedure
  6. 2002Front-load futures commission and slippage
  7. 2005Inactive account fees as hidden implementation cost
  8. 2010A pre-trade liquidity screen for futures contracts
  9. 2011Currency option venues, spreads, clearing, and premium cost
  10. 2012Filter futures contracts by liquidity and implementation cost
  11. 2012Futures commission versus one tick of cost
  12. 2012Ranking futures liquidity for executable orders
  13. 2013Filter option day trades by spread, volume, and fees
  14. 2013Filter futures by liquidity, open interest, and effective margin
  15. 2014Book futures data fees as implementation cost
  16. 2015Use a futures liquidity rank as a pre-trade checklist
  17. 2015Filter unexecutable futures by liquidity, open interest, and margin
  18. 2015Futures liquidity ranking as an execution filter
  19. 2015Filtering option trades by bid-ask width
  20. 2016Exchange quote fees as execution costs and liquidity filters
  21. 2016Filter futures by liquidity, open interest, and margin cost
  22. 2016Comparing dollar-index futures execution costs and liquidity
  23. 2016A futures liquidity ranking as a screen for executable orders
  24. 2017Filter a futures board by liquidity, open interest, and implementation cost
  25. 2017Filter futures contracts by liquidity and margin cost
  26. 2017How residency rules raise futures implementation costs
  27. 2018Screen listed futures by liquidity, open interest, and margin
  28. 2018Contract selection is the first filter on competing bitcoin futures
  29. 2018Filter futures execution by liquidity and margin
  30. 2018Commission analysis for brokerage execution costs
  31. 2019Ranking futures liquidity before you size the order
  32. 2020Brokerage selection as an implementation-cost problem
By fieldLiquidity and costs119 readingsBy year201585 readings
All 37 readings tagged Commission analysis
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