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1992issue C121-11

When stops change system timing

A stop or a profit target can force the book flat and thereby open later entries that the same signal would have skipped while a position was still open. The historical workflow therefore searches entry, stop and target together and still applies a hindsight penalty.

  • After a long trade is closed at a fixed dollar target, a later long signal may be taken that would have been ignored if the first position had still been open.
  • Stops can raise trade count over a fixed sample because they force the system flat and open slots for additional entries.
  • If the entry constant, stop amount and target amount can all vary, they should be searched jointly as three parameters, not treated as one entry rule.
  • If over-penalizing turns expected value negative, easing the parameter count just to restore a thin positive expectation is not accepted as proof the system is tradable.
Entries in this reading3 entries
Current trackRobustness testing58 readingsSystem optimization85 readingsStop-loss order144 readings

How the full rule set is scored

System optimization means jointly testing entry, stop and target settings as one procedure so the full rule set, not just the entry formula, is what gets scored.

A stop-loss is a pre-set exit that ends a losing or fully captured position and can leave the system flat, which may allow a later entry that would not have fired if the first trade were still open.

Robustness testing means checking whether a backtested rule set still looks usable after a hindsight penalty, instead of treating every extra control as free.

OEX five-day regression forecast oscillator, October 1991–January 1992

Traders watching a five-day %F on the OEX would have seen a routine plus-or-minus two band interrupted by a plunge near minus five on the mid-November break and a push above plus two as the late-December rally began. The readings were taken from the printed MetaStock pane; the letter never listed the daily values.
Traders watching a five-day %F on the OEX would have seen a routine plus-or-minus two band interrupted by a plunge near minus five on the mid-November break and a push above plus two as the late-December rally began. The readings were taken from the printed MetaStock pane; the letter never listed the daily values.OEX · daily · 1991-10-14T00:00:00.000Z to 1992-01-17T00:00:00.000Z

The letter hard-wires a five-period time-series forecast of the close, so each %F print is one hundred times (close minus the prior day's TSF) divided by close. The scan supports roughly half-point accuracy, not tick-level values.

How a stop or target changes later timing

A profit-target exit can change later timing. After a long trade is closed at a fixed dollar target, a subsequent long signal may be taken that would have been ignored if the first position had still been open.

Stops can raise trade count over a fixed sample because they force the system flat at times and thereby open slots for additional entries.

Count entry, stop and target together

If the entry constant, stop amount and target amount are all allowed to vary, they should be counted and searched jointly as three parameters rather than treated as a single entry rule.

If those same three settings are frozen forever across markets and periods, they may be treated as one parameter, but the resulting record still needs a hindsight penalty for having seen the past.

Any artificial control that restricts trading freedom consumes a parameter, regardless of how mild its effect on timing appears. Assigning fractional or fractal weights to interdependent parameters lacks a stated mathematical basis and is treated as an unjustified shortcut.

Parameter counting is used here to strip hindsight bias from simulated trading. If over-penalizing turns expected value negative, easing the count just to restore a thin positive expectation is not accepted as proof the system is tradable.

What a realistic stop is meant to do

A realistic stop is framed as an exit that ends a small loss before it becomes large. That includes a trailing stop a fixed percent below the highest price reached in the trade, which can be tightened as an open profit grows.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
12 of 51 in the Robustness testing track
19931-6 pp.Next on Robustness testingWalk-forward halt rules for forecast modelsTraining changes internal weights, while walk-forward recall emits outputs from unseen inputs with those weights frozen, so the two modes need mutually exclusive facts.
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 year1992115 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 controls1988Undisclosed rules block system robustness tests1988Walk-forward and neighborhood tests after optimization1989Binary search limits on multi-peak average grids