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2017issue C0358

Filter a futures board by liquidity, open interest, and implementation cost

A 2017 futures listing ranked contracts by value, a three-year price range, open interest, and a volume factor, then compared posted margin with effective margin. Editorial reading: treat that board as an execution menu so only markets with real activity, absorbable inventory, and a comparable implementation-cost rate remain.

  • A liquidity filter ranks listed futures by multiplying contract point value by a three-year maximum price move, then by open interest, then by a volume factor usually from one to four.
  • Relative activity can be shown as a descending mark count so markets with the densest marks sit above markets that show one mark or none.
  • Open interest becomes comparable when it is scaled by an equal-dollar-profit contract count that puts each market on the same dollar unit.
  • Effective percent margin divides posted margin dollars by the three-year dollar price range, then multiplies by one hundred, so posted margin can be compared with capital locked per unit of historical range.
Entries in this reading3 entries
Current trackCommission analysis37 readingsLiquidity filter118 readingsOpen interest analysis118 readings

Read the board as an execution menu

Editorial reading: treat a futures board as an execution menu. First apply a liquidity filter so only markets with real activity remain. Then read open interest as the inventory that can absorb the order. Finally convert posted margin into a comparable implementation-cost rate before choosing which contract is tradable.

The archive facts describe a historical ranking workflow. The three-step menu order is a TradersWeek interpretation and is not archive language.

Rank listed futures by activity

A futures liquidity ranking can be built by multiplying contract point value by a three-year maximum price move, then by open interest, then by a volume factor usually from one to four.

Relative contract liquidity multiplies that equal-dollar-profit contract count by total open interest and by a volume factor. The volume factor is the greater of one and the exponential of natural-log volume divided by natural-log 5000, minus two. That scalar usually sits between one and four and adjusts the liquidity score for unusually thin or unusually heavy volume.

Relative activity can be shown as a descending mark count so markets with the densest marks sit above markets that show one mark or none. In this workflow, the liquidity filter is that ranking: it screens listed futures by how readily size can be transacted, using activity marks built from contract value, a multi-year price range, open interest, and a volume scalar.

Scale open interest to a common dollar unit

An equal-dollar-profit contract count multiplies tick dollar value by the three-year maximum price excursion so each listed count represents the same dollar unit. It is the number of contracts of one market needed to match the same three-year dollar range as another market.

Open interest analysis uses outstanding contract inventory, scaled by that equal-dollar-profit contract count, as a measure of how much paper the market can absorb.

Compare posted margin with effective margin

Effective percent margin equals posted margin dollars divided by the three-year dollar price range of the contract, then multiplied by one hundred. Commission analysis compares posted percent margin with effective percent margin so capital locked per unit of historical dollar range is visible before an order is chosen.

In the 2017 listing, posted percent margin ran from 0.1 on short-rate futures to above 8 on some agricultural and currency contracts, while gold showed an effective percent margin of 33.9 against a posted 5.5.

A share-turnover counterpart in stocks

For stocks, period volume as a percentage of shares outstanding can be treated as a turnover-rate proxy for trading liquidity. Share turnover is equity volume over a period divided by shares outstanding.

Posted versus effective margin on the March 2017 futures board

Posted percent margin looks tiny in Eurodollars and short notes, but the effective rate — margin dollars over the three-year dollar price range — jumps into the teens. Energy and a few grains sit near parity, so those contracts do not get cheaper once the range is in the denominator. Figures are the March 2017 Stocks & Commodities liquidity table, carried over contract by contract.
Posted percent margin looks tiny in Eurodollars and short notes, but the effective rate — margin dollars over the three-year dollar price range — jumps into the teens. Energy and a few grains sit near parity, so those contracts do not get cheaper once the range is in the denominator. Figures are the March 2017 Stocks & Commodities liquidity table, carried over contract by contract.Listed U.S. commodity futures · March 2017 listing · 2014-01-01T00:00:00.000Z to 2017-12-31T00:00:00.000Z

Effective percent margin is posted margin dollars divided by the contract’s three-year dollar price range, times 100. Contracts stay in the source’s relative-liquidity order. Most listings are the March 2017 expiry; Eurodollar is December 2017 and a few livestock, metals, and rates use February or April.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
24 of 32 in the Commission analysis track
201758-58 pp.Next on Commission analysisFilter futures contracts by liquidity and margin costEditorial: keep a futures market out of the idea notebook until it clears activity marks, an open-interest-scaled size check, and a margin-versus-range cost comparison.
All readings on this track · 32 readings
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  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
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  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
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  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 year2017100 readings
All 37 readings tagged Commission analysis
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