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2018issue C048-11

Point-in-time universes for system evaluation

A ten-year Nasdaq 100 evaluation of the same entry and exit rules changed when a trade was allowed only if the name was an index member on the signal date. Scoring later surviving constituents is survivorship-bias.

  • The first run applied the demonstration rules to the Nasdaq 100 membership that existed at test time, not to the membership that existed on each historical signal date.
  • A second run allowed a trade only when the name was an index member on the signal date, and that universe change altered the reported evaluation metrics.
  • Scoring a historical portfolio on later surviving constituents embeds knowledge of which names remained in the index, a construction error called survivorship-bias.
  • A less biased construction needs dated constituent history that includes later-delisted names plus the actual addition and removal dates.
Entries in this reading3 entries
Current trackRobustness testing58 readingsSystem optimization85 readingsWalk-forward analysis95 readings

The demonstration rules and capital constraints

The demonstration rules entered after four consecutive down closes and exited after two consecutive up closes.

The evaluation used a ten-year window, 100000 starting capital, and 10 percent of current equity per position on Nasdaq 100 names.

Membership at test time is not a point-in-time-universe

The first run applied those rules to the Nasdaq 100 membership that existed at test time, not to the membership that existed on each historical signal date.

A second run of the same rules allowed a trade only when the name was an index member on the signal date, and that universe change altered the reported evaluation metrics.

Index-reconstitution and dated constituent history

Nasdaq 100 membership changed many times in the sample that began in 2007, including 24 December 2012, when ten names left and ten entered.

Those additions and removals are index-reconstitution: they change who belongs to an index during the evaluation window.

A less biased construction needs dated constituent history that includes later-delisted names plus the actual addition and removal dates.

The point-in-time-universe is the eligible name set that existed on the date a signal, size, or abstention decision is scored.

The same lookahead error can occur without an official index if names are chosen with knowledge of how they later performed.

Editorial reading of the evaluation-procedure

Editorial: walk-forward analysis, robustness testing, and system optimization cannot validate entry, exit, and sizing rules if the historical tradable universe is rebuilt with knowledge of later survivors.

Editorial: the evaluation-procedure is the combined test of entry, exit, abstention, position size, and eligibility under stated capital and data constraints. It is not complete until eligibility is scored on a point-in-time-universe.

Editorial: the second run is the robustness-check, which re-runs the same signal rules after correcting universe construction to see whether the evaluation still holds.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
48 of 51 in the Robustness testing track
201844-45 pp.Next on Robustness testingWalk-forward robustness evaluation for optimized systemsChoose which rule inputs may be searched, reserve later data the search cannot see, and keep the rules only if they still emit coherent signals after costs and competing objectives.
All readings on this track · 51 readings
  1. 1986Degrees of freedom in trading system optimization
  2. 1988Walk-forward and neighborhood tests after optimization
  3. 1988Undisclosed rules block system robustness tests
  4. 1988Testing re-optimization calendars against random parameter controls
  5. 1989Binary search limits on multi-peak average grids
  6. 1989Parameter neighborhoods that survive a shift
  7. 1990Use profit mapping to keep a cycle and stop plateau
  8. 1990Why popular indicator optimization fails robustness
  9. 1991Retesting weighted indicator balances across horizons
  10. 1992Constructing forecast models with regression, walk-forward, and robustness
  11. 1992Diagnose regimes before you lock parameters
  12. 1992When stops change system timing
  13. 1993Walk-forward halt rules for forecast models
  14. 1994Walk-forward evaluation of genetic index rules
  15. 1995Input pruning as walk-forward system evaluation
  16. 1995Critiquing neural nets as incomplete trading systems
  17. 1996Rebuild the equity-path ratio before it ranks a designed system
  18. 1996Parameter grids can fit random walks
  19. 1996Walk-forward analysis belongs in the design of a mechanical trading system
  20. 1997When a holdout fails, discard the rule set
  21. 1997Test rewarded rule breaks before replacing the system
  22. 1997Walk-forward rules keep system research from rewriting live trades
  23. 1999Keep a channel-breakout to two lookbacks and test neighbor stability
  24. 1999Constant investment size in stock system evaluation
  25. 2000Forcing optimization maps mechanical system failure boundaries
  26. 2000Robust parameter selection with surface charts
  27. 2001A two-gate classroom test for a two-window momentum trend filter
  28. 2002How a two-sided continuation factor becomes a testable trend rule
  29. 2002Evaluating two-window trend intensity as a reversal rule
  30. 2003Discounting speculative bubbles in system robustness tests
  31. 2003Walk-forward evaluation of locked stochastic oscillator rules
  32. 2003Critiquing mechanical system design after extreme price regimes
  33. 2004Evaluating a two-window trend trigger
  34. 2005Grade backtested signals with holdouts and optimization plateaus
  35. 2006Reserved-sample evaluation of trading system design
  36. 2006Walk-forward critique of hindsight crossover systems
  37. 2008Condition-matched walk-forward evaluation for mechanical systems
  38. 2011Session-split evaluation of regular and overnight systems
  39. 2012Walk-forward evaluation as operator rehearsal
  40. 2013Two-window evaluation of mechanical trading systems
  41. 2013Walk-forward filter selection for repeated-median velocity
  42. 2014Walk-forward evaluation for fading-memory velocity systems
  43. 2015Test oscillator events before tuning rules
  44. 2016Walk-forward evaluation of a five-parameter parabolic stop-and-reversal
  45. 2016Walk-forward optimization without curve fitting
  46. 2017Optimization without overfitting in trend-system evaluation
  47. 2017Parameter stability is a better guide than a larger crossover grid
  48. 2018Point-in-time universes for system evaluation
  49. 2018Walk-forward robustness evaluation for optimized systems
  50. 2018Critiquing breakout systems through robustness tests
  51. 2018A critique of parameter fitting in system design
By fieldSystem design117 readingsBy year201898 readings
All 58 readings tagged Robustness testing
Also on Robustness testing5 readings
1986Degrees of freedom in trading system optimization1988Testing re-optimization calendars against random parameter controls1988Walk-forward and neighborhood tests after optimization1992Diagnose regimes before you lock parameters1993Walk-forward halt rules for forecast models