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2016issue C0210-12

Three-layer confirmation: adaptive average, stochastic relative strength index, and stop-and-reverse

A confirming combination of three indicators is presented for foreign-exchange and equity charts. An adaptive moving average sets a buy or sell zone, a stochastic reading of the relative strength index marks overbought and oversold bands, and a stepped stop-and-reverse overlay refines entry and exit after those layers are in place.

  • The first layer is an adaptive moving average used as a trend filter that splits the chosen time frame into a buy zone above the line and a sell zone below it.
  • The second layer applies the stochastic oscillator to relative-strength-index values, producing a reading from zero to one that two thresholds then split into overbought, mid, and oversold bands.
  • The third layer is a stop-and-reverse overlay that plots in steps from the period average of highs and the period average of lows, used after trend and oscillator context are set to refine entries, exits, and short-term pullbacks.
  • Convergence is the decision rule: several independent indicator readings must agree on the same directional conclusion before a trade plan is treated as complete.
Entries in this reading3 entries
Current trackAdaptive moving average28 readingsStochastic oscillator170 readingsRelative Strength Index186 readings

A confirming combination for two markets

A confirming combination of three indicators is presented as applicable to both foreign-exchange and equity charts. The layers are meant to be read in order: first a zone from an adaptive moving average, then an exhaustion reading from a stochastic transform of the relative strength index, then a stepped stop-and-reverse overlay that refines entry and exit.

Layer one: adaptive moving average

The first layer is an adaptive moving average used to classify the chosen time frame into a buy zone above the average and a sell zone below it. That adaptive average is defined as a smoothed moving average lying between a double exponential moving average and an exponential moving average, with signals generated in the same manner as other moving averages.

Layer two: a stochastic reading of the relative strength index

The second layer applies the stochastic-oscillator formula to relative-strength-index values, producing a reading that ranges from zero to one. The relative strength index is the ordered-price series that this range-normalization is applied to, so the combined oscillator is bounded.

Two horizontal thresholds divide that oscillator into three bands. A break of the upper band is treated as overbought and a break of the lower band as oversold. Each break is associated with an expected turn or correction.

Layer three: stop-and-reverse overlay

The third layer is a stop-and-reverse indicator that plots in steps from the period average of highs and the period average of lows. It is used to refine entry and exit after trend and oscillator context are set. On that overlay, price above the upper step during an uptrend is treated as a continuation condition, while candles beneath the lower step are treated as a short-term pullback inside a buy zone.

Convergence as the decision rule

The intended decision rule is convergence. Several independent indicators must point to the same directional conclusion before a trade plan is treated as complete.

USD/CHF hourly price versus Tillson’s T3 average

After the late-October lift, hourly USD/CHF stays above Tillson’s T3, which this stack treats as the buy zone; price had been below the average at the left of the window. Levels were read from the published one-hour USD/CHF figure (18 October–29 November 2015), not from a table.
After the late-October lift, hourly USD/CHF stays above Tillson’s T3, which this stack treats as the buy zone; price had been below the average at the left of the window. Levels were read from the published one-hour USD/CHF figure (18 October–29 November 2015), not from a table.USD/CHF · 1 hour · 2015-10-18T00:00:00.000Z to 2015-11-29T00:00:00.000Z

Visual readings are approximate to about 0.001 in the rate. The platform quote box on the figure prints a last price of 1.03264.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
18 of 24 in the Adaptive moving average track
201750-56 pp.Next on Adaptive moving averageOne-alpha reverse-path exponential smoothingA seed-smoother on closing prices uses a complementary-weight equal to one minus alpha, then eight reverse-path-stages mix each current reverse value with its prior bar at successive powers of two through 128.
All readings on this track · 24 readings
  1. 1991Building variable-length moving averages from partitioned price changes
  2. 1991Variable-length moving average from change dispersion
  3. 1992Constructing volatility-adaptive exponential smoothing
  4. 1995Constructing an adaptive moving average with an efficiency ratio and filter
  5. 1995Two-gate breakout confirmation with adaptive averages
  6. 1995Building momentum-scaled adaptive moving averages
  7. 1995Adaptive length as a construction choice inside exponential smoothing
  8. 1998Testing price-channel breakouts with a lag-aware adaptive average
  9. 1998Constructing filters by nesting offsets and variable weights
  10. 1998Constructing an efficiency ratio adaptive average and entry filter
  11. 2001Encoding candle structure as a numeric filter
  12. 2001Adaptive averages driven by cycle-phase speed
  13. 2005Constructing an adaptive moving average from a fractal-dimension weight
  14. 2005Range-dimension adaptive exponential filter
  15. 2010Constructing simple, exponential, and adaptive averages
  16. 2010How a price-hugging smoother is assembled from ordinary averages
  17. 2013Evaluating an adaptive moving average against a same-window moving average
  18. 2016Three-layer confirmation: adaptive average, stochastic relative strength index, and stop-and-reverse
  19. 2017One-alpha reverse-path exponential smoothing
  20. 2018Pair two adaptive averages to filter swing turns
  21. 2018Two Adaptive moving averages as a confirmation pair
  22. 2018Constructing an adaptive filter for adoption-cycle reversals
  23. 2018Constructing a deviation-scaled adaptive moving average
  24. 2020Walk-forward and adaptive averages as two tests of the same trend
By fieldIndicators and filters682 readingsBy year201678 readings
All 28 readings tagged Adaptive moving average
Also on Adaptive moving average5 readings
1995Adaptive length as a construction choice inside exponential smoothing1991Building variable-length moving averages from partitioned price changes1991Variable-length moving average from change dispersion1992Constructing volatility-adaptive exponential smoothing1992Constructing volatility-adaptive trailing stops