Skip to main content
Track Walk-forward analysis
19 / 50
Library

1997issue C111-9

A walk-forward check for bond-breadth timing

A utilities-plus-breadth combination that looked strong on a fitted 10-year daily sample failed on held-out data and was discarded as curve-fitting. The replacement mechanical trading system froze independent buy and sell rules on T-bond direction and NYSE issue and volume ratios, then treated agreement across a predeclared test window and two holdouts as necessary confidence.

  • A utilities-plus-breadth combination that looked strong on a fitted 10-year daily sample failed on held-out data and was discarded as curve-fitting.
  • The later mechanical trading system used the S&P 500, continuous T-bond futures, and NYSE issue and volume ratios, with buy and sell conditions specified independently.
  • Fourteen parameters were searched on a predeclared test window, with earlier and later segments held out. Fitted-sample results alone were described as unusable for forecasting.
  • Similar results on test and held-out segments were treated as necessary confidence, not as a guarantee of later behavior.
Entries in this reading3 entries

The first fit was discarded

The archive first combined utilities with market breadth. That combination looked strong on a fitted 10-year daily sample, then failed on held-out data and was discarded as curve-fitting.

After that failure, a continuous T-bond futures series replaced the utilities series. Because those futures began trading in 1977, earlier history could not be examined.

What the replacement rules used

The mechanical trading system takes the S&P 500, continuous T-bond futures, and daily NYSE advancing and declining issues and volume as inputs. Those counts are converted into issue and volume ratios so earlier periods remain comparable after NYSE listings more than doubled from 1978 and volume later reached about 10 times the 1978 level. Market breadth is carried as advancing issues divided by declining issues, and as the matching volume ratio.

T-bond quotes are treated as price of par, so a rising smoothed futures price is read as falling yields. Daily futures are exponentially smoothed with the two-day constant 2/(1+2). T-bond direction is the smoothed bond-futures price minus its value a chosen number of days earlier.

Buy and sell conditions are specified independently. Both require persistent T-bond direction, breadth or volume-ratio thresholds, and an S&P 500 move of a set percentage from a local extreme before a close entry or exit.

The predeclared split

Fourteen parameters were searched after the sample from January 3, 1978 through August 8, 1997 was split into a January 2, 1987 to December 29, 1995 test window and held-out windows of January 3, 1978 to February 27, 1987 and January 3, 1996 to August 8, 1997.

All 14 parameters could not be searched at once. Buy and sell groups were optimized separately in batches of up to four variables, with later passes using the previous groups' selected values.

Similar results on test and held-out segments were treated as necessary confidence, not as a guarantee of later behavior. Fitted-sample results alone were described as unusable for forecasting.

A sell rule that could not exit quickly

The selected sell-direction rule required 11 consecutive down days in smoothed T-bond direction. That left about a two-week interval in which no exit could fire. Late exits in the full sample were blamed on decline-advance issue or volume ratios not triggering, including a March 29, 1994 exit 6.1% below the February 2, 1994 peak.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
19 of 50 in the Walk-forward analysis track
19981-10 pp.Next on Walk-forward analysisWalk-forward audit of regression trend forecastsA least-squares line through a finite run of daily closes is extended one sampling interval ahead to plot a next-close forecast.
All readings on this track · 50 readings
  1. 1990Three-window walk-forward system evaluation
  2. 1990Building the construction layer of a mechanical trading system
  3. 1991Constructing walk-forward neural trading rules
  4. 1991Constructing neural trading systems from facts to walk-forward
  5. 1992Walk-forward evaluation of stop overlays on average crossovers
  6. 1992Audit mechanical system tests for fills and regimes
  7. 1993Walk-forward evaluation of monthly yield and real-rate forecasts
  8. 1993Constructing walk-forward forecasts with linear and moving-average baselines
  9. 1993Walk-forward hybrid rules for intermarket forecast stacks
  10. 1994Neural-net construction as a mechanical trading-system problem
  11. 1995Constructing an intermarket neural net trading system
  12. 1996Weekly market breadth as one procedure on an unused window
  13. 1996Walk-forward evaluation of gold-index bond-fund rules
  14. 1996Evaluating weekday-in-month filters for index day trades
  15. 1996Require both a trend filter and a cycle oscillator before entry
  16. 1997Walk-forward windows as a diagnostic of parameter instability
  17. 1997Walk-forward validation of a market-breadth timing rule
  18. 1997Sunspot spikes and walk-forward evaluation of an adaptive cycle rule
  19. 1997A walk-forward check for bond-breadth timing
  20. 1998Walk-forward audit of regression trend forecasts
  21. 1998Evaluating a cubic least-squares currency trend with walk-forward segments
  22. 1998Walk-forward evaluation of recursive yen trend signals
  23. 1999Personal system design under crowd psychology
  24. 1999Walk-forward evaluation of a polynomial price forecast
  25. 2000Walk-forward optimization of regression-slope-angle rules
  26. 2001Construct a winter seasonal window as one procedure
  27. 2001Inspectable rules when system write-ups dry up
  28. 2002Evaluating mechanical systems before position sizing
  29. 2003Walk-forward construction of rule-based market-position systems
  30. 2007Evaluating metal seasonal windows across regimes
  31. 2007Evaluating mechanical timing systems against hold baselines
  32. 2011Walk-forward reoptimization as a system design gate
  33. 2011Evaluate generated systems on holdouts, then add stops
  34. 2012Walk-forward analysis and out-of-sample tests for a mechanical trading system
  35. 2012Personality-first trading system design
  36. 2012Scorecard-first mechanical system construction
  37. 2012Constructing an advancer-decliner moving average for market breadth
  38. 2012Formula search as mechanical system construction
  39. 2013Identity-first system construction
  40. 2013Construct a swing system from bias rules to walk-forward
  41. 2014Evaluate mechanical stock systems with stops and walk-forward
  42. 2014Walk-forward velocity filters on noisy intraday trends
  43. 2015Event-predictability versus position-constrained rules
  44. 2015Constructing mechanical systems for walk-forward tests
  45. 2016When a tested system must be retired
  46. 2016Walk-forward metric filters and chance-level checks for selected inputs
  47. 2018Evaluate mechanical trading systems without catalog rankings
  48. 2019Phased stop construction from entry risk to trailing exit
  49. 2020Stockpiling simple ideas for mechanical system construction
  50. 2020A pretty first draft is not a walk-forward waiver
All 95 readings tagged Walk-forward analysis
Also on Walk-forward analysis5 readings