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2017issue C0658

Filter futures contracts by liquidity and margin cost

An archive listing ranks futures by activity dots, open-interest-scaled size, and margin versus a three-year dollar range. Editorial: treat those marks as an execution screen before a market enters the idea notebook.

  • Editorial: 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.
  • Relative contract liquidity appears as activity dots: more dots mean heavier trading, one dot or none means little activity, and markets at the top of that order are the easiest to buy and sell.
  • Equal-dollar contract count scales listed markets to the same three-year dollar opportunity. Effective percent margin is dollar margin divided by the three-year dollar price range, then multiplied by 100.
  • Each column is a proportional comparison and is meaningful only against other values in the same column.
Entries in this reading3 entries

Contract selection as an execution screen

The archive workflow ranks listed futures before they are treated as executable. Liquidity is marked with activity dots. Size is scaled to a common dollar opportunity. Margin is compared with the contract three-year dollar price range.

Editorial: teach contract selection as an execution screen first. A market may enter the idea notebook only after it clears activity marks, an open-interest-scaled size check, and a margin-versus-range cost comparison.

Editorial: those three checks map to a Liquidity filter on activity, an Open interest analysis on scaled size versus outstanding positions, and a Commission analysis on implementation cost through effective percent margin. Each is used to choose an executable order and account for implementation cost.

Activity marks and relative contract liquidity

The futures comparison marks relative liquidity with a count of activity dots. More dots mean heavier trading, and one dot or none means little activity. Relative contract liquidity is a cross-market rank built from equal-dollar contract count, open interest, and a volume adjustment, shown as activity marks from easiest to hardest to trade.

That liquidity rank multiplies contract point value, a three-year maximum price move, open interest, and a volume factor usually set between 1 and 4. The archive also defines relative contract liquidity as the equal-dollar contract count times total open interest times a volume factor equal to the greater of 1 or exp(ln volume / ln 5000 - 2).

Markets at the top of the liquidity order are the easiest to buy and sell and those at the bottom the hardest.

Scaled size and effective percent margin

The equal-dollar-profit contract count equals tick dollar value times the three-year maximum price excursion, so listed markets are scaled to the same dollar opportunity. Equal-dollar contract count is how many contracts of one market must be traded to match another market three-year dollar price excursion.

Effective percent margin equals dollar margin divided by the three-year dollar price range of the contract, then multiplied by 100. It is used to compare capital locked per unit of historical range.

A June 2017 listing

In the June 2017 listing, the S&P 500 E-mini showed a 4.4 percent margin, a 17.9 effective percent margin, and a 2-contract equal-dollar count, while Eurodollar required 22 contracts and the Japanese yen showed a 35.6 effective percent margin.

Share turnover as an equity proxy

For listed shares, activity used as a liquidity proxy is period volume expressed as a percentage of shares outstanding, which is the share turnover rate.

Posted and effective percent margin, June 2017 futures

Each pair of bars is one row from the June 2017 Technical Analysis of Stocks & Commodities futures-liquidity table, kept in that listing’s liquidity order. The primary series is effective percent margin (exchange margin dollars divided by the contract’s three-year dollar range); the reference series is posted percent margin. Yen, silver and gold lock up a large share of the three-year range as margin, while WTI, Brent, lean hogs and hard red wheat screen cheaper on that range-adjusted test even when posted margin looks similar. Rates and eurodollars look cheap on the posted column but not once margin is scaled to range.
Each pair of bars is one row from the June 2017 Technical Analysis of Stocks & Commodities futures-liquidity table, kept in that listing’s liquidity order. The primary series is effective percent margin (exchange margin dollars divided by the contract’s three-year dollar range); the reference series is posted percent margin. Yen, silver and gold lock up a large share of the three-year range as margin, while WTI, Brent, lean hogs and hard red wheat screen cheaper on that range-adjusted test even when posted margin looks similar. Rates and eurodollars look cheap on the posted column but not once margin is scaled to range.Listed U.S. futures, front-month as of the June 2017 listing · June 2017 listing

Rows follow the printed relative-liquidity ranking (activity dots are not converted to a series). Effective percent margin is margin dollars divided by the three-year dollar range of the contract, times 100. Both percent columns are proportional measures and are meant to be compared across rows of the same listing, not read as standalone hurdle rates.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
25 of 32 in the Commission analysis track
201727-27 pp.Next on Commission analysisHow residency rules raise futures implementation costsEditorial: run commission-analysis only after asking which desks are allowed to hold the account. A route no permitted desk can work is not executable, whatever the displayed book shows.
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
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