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2017issue C1118-21

A fractal-dimension regime-gate for mechanical breakout entries

Fractal dimension converts a recent price path into a trending, random, or cyclic label. A mechanical breakout procedure can require that label to confirm the chart condition and can treat a conflict as a no-trade zone.

  • A fractal dimension near 1 is treated as a trend-like line, near 1.5 as random or Brownian, and nearer 2 as a more cyclic, space-filling path. The Hurst exponent converts to that label by D = 2 - H.
  • On a 64-day window ending May 26, 2017, an arbitrary band of 1.45 to 1.55 labeled about 50 percent of S&P 500 names as random, about 30 percent as trending, and about 20 percent as cyclic.
  • Whether a name looks random or partly predictable depends on the estimator, the window length, and the asset, so different stocks can sit in different regimes on the same date.
  • A double-confirmation-breakout fires only when the price-structure breakout and the regime-gate agree. Conflicting colors or classes define a no-trade zone.
Entries in this reading3 entries

Start with the regime class

The historical workflow first measures how space-filling the recent price path has been. Fractal dimension supplies a fractional label for that window: trending, random, or cyclic, rather than a Euclidean line, plane, or solid.

That class is then available to a mechanical entry as market state. The breakout remains a price-structure condition. The label is what allows the condition to become a signal, or what withholds it.

How fractal dimension becomes a label

A price path with fractal dimension near 1 behaves like a line and is treated as trend-like. A value near 1.5 is treated as random or Brownian. A value nearer 2 is treated as a more space-filling, cyclic figure.

The Hurst exponent is a persistence statistic related to fractal dimension by D = 2 - H. Values of H away from one-half imply memory or anti-persistence in the path. A Hurst estimate can be converted directly into a regime label.

An arbitrary band on one window

On a 64-day window ending May 26, 2017, an arbitrary band of 1.45 to 1.55 classified S&P 500 names as random. Values below 1.45 were labeled trending. Values above 1.55 were labeled cyclic.

Under those same cutoffs, about 30 percent of S&P 500 stocks were labeled trending, 50 percent random, and 20 percent cyclic. Most names were not in a trend class.

The same date can hold several regimes

Whether a given stock looks random or partially predictable depends on the fractal-dimension estimator, the length of the time window, and the asset. Different names can sit in different regimes at the same calendar date.

Estimators that a rule engine can refresh

Classical rescaled-range analysis estimates the Hurst exponent by breaking logarithmic daily returns into successively larger non-overlapping power-of-two segments, averaging R/S, and taking the slope of log(R/S) versus log(segment length).

A two-segment high-low slope method and a finer true-range method both estimate fractal dimension from OHLC structure. The true-range-slope-estimator substitutes mean true range times n for summed segment slopes and the window range over n for the full-window slope.

Those shortcuts exist because full rescaled-range work is laborious at a single date and does not readily produce a moving daily Hurst or fractal-dimension series for a live rule engine.

Double confirmation and the no-trade zone

A mechanical entry procedure can require double confirmation of a breakout with the regime direction. The price-structure breakout and the regime-gate must agree before a signal is issued.

Conflicting colors or classes are treated as an explicit no-trade zone rather than forced into a signal.

Editorial: TradersWeek treats that no-trade zone as abstention inside the same testable procedure as the entry, not as a missing signal.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
17 of 20 in the Breakout confirmation track
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All readings on this track · 20 readings
  1. 1982Constructing a funnel from converging support and resistance
  2. 1990Bond trends as auction tests at prior highs
  3. 1995Constructing mechanical trendline breakout entries
  4. 2000Crowd balance points before a range-breakout
  5. 2000Breakout rules fail without tested exits
  6. 2002Waiting for setups instead of forcing trades
  7. 2003The 20-day channel high as a support test after breakout
  8. 2004Intermediate-term breakout rules and fifty-day exits
  9. 2004A three-check drill for support and resistance
  10. 2004Weekly exponential averages turn from breakout rails to resistance
  11. 2005Constructing a three-state moving-average breakout histogram
  12. 2005A three-state directional breakout on a moving-average midline
  13. 2005A range-market breakout watchlist with 50-day pullbacks and stops
  14. 2009Optimism bias, breakout adds, and predefined loss limits
  15. 2015Refuse mixed-horizon entries until the checklist locks one persona
  16. 2017Intraday breakouts planned from whole-number support and resistance
  17. 2017A fractal-dimension regime-gate for mechanical breakout entries
  18. 2018Trend-first FX walls stay a hypothesis until a second touch, RSI recross, or failed break
  19. 2019Constructing a sell-relative-strength-index from the intrabar range ratio
  20. 2020Decluttered charts for breakout, support, and stop rules
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