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2012issue C0512-17

Sentiment-zone oscillator from signed closes

Code each bar as plus one after a higher close and minus one otherwise, then take a lookback-period triple exponential moving average of those signed closes and scale it by 100 divided by the same period. A 14-bar default uses extremes above 7 and below -7 rather than a zero line, and a longer high-low range of the oscillator can replace those fixed bands.

  • Each bar is coded plus one after a higher close and minus one otherwise, so the input series encodes only the direction of consecutive closes.
  • Sentiment position is the lookback-period triple exponential moving average of those signed closes, then scaled by 100 divided by the same period.
  • The default 14-bar construction treats readings above 7 and below -7 as contrary extremes. Zero is not used as a signal line.
  • A longer-window high-low range of the oscillator can replace the fixed 7 and -7 bands, and illustrated system code then combines those extremes with a 30-bar average of the oscillator and a 60-bar exponential average of price.
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Current trackExponential smoothing183 readingsTrend filter184 readingsMoving average597 readings

Code only the direction of consecutive closes

Each bar is coded plus one after a higher close and minus one otherwise, so the input series encodes only the direction of consecutive closes.

Sentiment position is the lookback-period triple exponential moving average of those signed closes, then scaled by 100 divided by the same period. That exponential smoothing applies a triple exponential moving average to the plus-one or minus-one close series so the sentiment position reacts to recent signed closes without treating every day equally.

Use extreme thresholds, not a zero line

The default construction uses a 14-bar period and treats readings above 7 as one extreme and readings below -7 as the opposite extreme. Zero is not used as a signal line in the base construction. Only the extreme thresholds define the contrary conditions.

DJIA 14-bar sentiment zone oscillator with ±7 rails

Tags of the upper rail mark extreme optimism and tags of the lower rail mark extreme pessimism; this DJIA daily window shows four such contrary signals. Oscillator readings were digitized from the plotted SZO pane, with the closing 5.17 taken from the value printed on the chart.
Tags of the upper rail mark extreme optimism and tags of the lower rail mark extreme pessimism; this DJIA daily window shows four such contrary signals. Oscillator readings were digitized from the plotted SZO pane, with the closing 5.17 taken from the value printed on the chart.DJIA · daily · 2007-07-01T00:00:00.000Z to 2008-04-25T00:00:00.000Z

Default lookback is 14 bars. With that length the oscillator cannot reach ±100, so the source uses +7 and -7 as the extreme rails and ignores the zero line. Intermediate readings are approximate to the raster; only the final 5.17 is a printed figure.

Replace fixed bands with a longer high-low range

A longer-window high-low range of the oscillator can replace the fixed 7 and -7 bands with adaptive overbought and oversold levels.

Ask longer filters to agree with the extremes

The illustrated trading-system code combines the oscillator extremes with a 30-bar average of the oscillator and a 60-bar exponential average of price as agreement filters.

That moving average is a simple average of the sentiment-zone series over a longer window, used as a directional filter rather than a price smoother. The trend filter is a higher-timeframe directional gate, typically an exponential average of price or a moving average of the oscillator, that allows only those extreme crossings that agree with the prevailing drift.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
35 of 41 in the Exponential smoothing track
20128-11 pp.Next on Exponential smoothingClassic RSI one-over-N smoothing versus the standard exponential averageThe classic RSI update weights the newest observation by 1/N, while the usual price exponential average uses 2/(N+1).
All readings on this track · 41 readings
  1. 1984Matching average age across price filters
  2. 1984Residual-impact construction of exponential smoothers
  3. 1988Constructing simple and exponential moving averages as specified filters
  4. 1989Evaluating smoothed free reserves and funds-discount spreads
  5. 1990Integer construction of moving averages and exponential smoothing
  6. 1990Constructing incremental moving average filters
  7. 1991Constructing a double-smoothed stochastic oscillator
  8. 1991Constructing an exponential average from a smoothing weight
  9. 1991Constructing a double-smoothed momentum oscillator family
  10. 1991Competing certainty rules from exponential-average conditions
  11. 1991Hybrid construction of a mechanical timing system from smoothed signals
  12. 1991Constructing an exponential smoother from a moving-average length
  13. 1991Equivalent relative-strength-index constructions from a ratio and from smoothed momentum
  14. 1991Constructing the true strength index from double-smoothed momentum
  15. 1991True strength index from signed, double-smoothed momentum
  16. 1992Constructing exponential averages from simple lookbacks
  17. 1992Constructing exponential averages by the smoothing constant, startup length and lag
  18. 1992Nested range smoothing and windowed high-low damping
  19. 1992A weekly equity stance from the discount-bill spread
  20. 1993Double-smoothed stochastics momentum index construction
  21. 1993Constructing the true strength index with double exponential smoothing
  22. 1994Polarized fractal efficiency with a shared exponential smoother
  23. 1994Five-interval exponential smoothing of ten-interval signed path-efficiency
  24. 1994Hand-ranked price-volume series with stacked smoothing and stochastic
  25. 1995Range expansion filter on multi-horizon averages
  26. 1995The exponential smoothing constant from averaging lag
  27. 1997Construct a nested-average rainbow band and oscillator
  28. 1998Filter stacks that combine a moving average with exponential smoothing
  29. 2002Smoothed relative-strength construction from wilder-averaging and a price prefilter
  30. 2003Reverse-engineered RSI price targets
  31. 2004Piecewise trend quality from moving-average reversals
  32. 2004Nested smoothing recipes versus unaudited oscillator experiments
  33. 2008Weight construction beyond the N-day label
  34. 2010A consensus filter for objective RSI and smoothing construction
  35. 2012Sentiment-zone oscillator from signed closes
  36. 2012Classic RSI one-over-N smoothing versus the standard exponential average
  37. 2013Why exponential smoothing uses two over n plus one
  38. 2015Constructing ratio indicators with moving-average and exponential-smoothing weights
  39. 2015Slow relative-strength index from an exponentially smoothed price
  40. 2017Rebuilding the relative strength index as open-scale buy-sell pressure
  41. 2017Comparing Wilder and exponential smoothing inside a relative-strength index
By fieldIndicators and filters874 readingsBy year2012165 readings
All 183 readings tagged Exponential smoothing
Also on Exponential smoothing5 readings
1984Matching average age across price filters1995Range expansion filter on multi-horizon averages1997Construct a nested-average rainbow band and oscillator2004Piecewise trend quality from moving-average reversals1989Alpha-beta lag parameters versus moving-average windows