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2017issue C047

Constructing weighted Bollinger bands and volume averages

Exponential-standard-deviation-bands use an exponentially weighted average as the midline-estimator and as the series for dispersion-width. The same pattern has been applied with other weightings, and a volume-weighted-moving-average is defined for use as a breakout baseline.

  • Exponential-standard-deviation-bands place an exponentially weighted average at the center and compute dispersion-width from that same series.
  • The same midline-estimator and dispersion-width pattern has been applied with weighting methods other than the exponential case.
  • A volume-weighted-moving-average is the lookback-length sum of volume times closing price divided by the lookback-length sum of volume.
  • That volume-weighted average appears in a breakout-indicator discussion, and alternative trend or volatility estimators are presented as worth comparing on their own merits.
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Current trackBollinger Bands84 readingsMoving average449 readings

Building the exponential band

An exponential-standard-deviation-bands construction uses an exponentially weighted average as the center line and also as the series from which standard-deviation width is computed. That exponential band construction is described as already more than 20 years old at the time of the correspondence.

The same construction pattern, a weighted average as midline-estimator and as the input to dispersion-width, has been applied with other weighting methods besides the exponential case.

Other estimators on their own merits

Alternative band formulations that change the trend estimator or the volatility estimator are presented as worth comparing on their own merits.

A volume-weighted breakout baseline

A volume-weighted-moving-average is defined as the lookback-length sum of volume times closing price divided by the lookback-length sum of volume. One scripted implementation of that volume-weighted average uses a length input of 12.

The volume-weighted average appears in a breakout-indicator discussion, and a reader asked how to obtain or script it on a charting platform.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
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201749-56 pp.Next on Bollinger BandsFour swing-entry rules that share a timed exitWith fills and the holding period held fixed, the four detectors can be rotated so a pivot, a band touch, and two relative strength index rules mark turning points on the same bars.
All readings on this track · 45 readings
  1. 1992Constructing volatility-scaled bands with relative strength index confirmation
  2. 1994Implied volatility as a band-defined regime filter for index options
  3. 1995Constructing projection bands from least-squares slopes
  4. 1995Constructing regression projection bands and range oscillators
  5. 1996Constructing Bollinger bands, percent-b, and stochastics
  6. 1996Constructing mechanical rules from Bollinger Bands and stochastics
  7. 1996Constructing a standard-error envelope around a linear regression
  8. 1996Dual-horizon ratio envelopes and regression error channels
  9. 1997Rational group structure with a trend screen, RSI, and bands
  10. 1997Asymmetric volatility band construction
  11. 1998Constructing three-state filters from Bollinger band envelopes
  12. 1999Combination filters with Bollinger Bands and the relative strength index
  13. 1999Constructing stochastic timed exits and band-RSI reversals
  14. 1999Evaluating Bollinger Bands against fixed-width and range-based envelopes
  15. 2000Constructing a Bollinger Band target as a forward price
  16. 2001Numeric candlestick encoding with local size bands
  17. 2001Ranked candlestick sentiment to band-cross entries
  18. 2002Combining Bollinger Bands, RSI, and a stop-loss
  19. 2002Bollinger Bands remain filters, not forecasts
  20. 2002Constructing a stochastic RSI with Bollinger bands
  21. 2002Constructing a StochRSI and Bollinger mechanical system
  22. 2003Constructing volatility-scaled Bollinger envelopes
  23. 2003Why tick breadth fails as a market personality
  24. 2005Constructing Bollinger bands versus fixed trading bands
  25. 2006Squared versus absolute deviation in envelope construction
  26. 2006Confirming yen crossovers with implied volatility and bands
  27. 2006A daily candle reversal is a hypothesis until shorter sessions fail at the same zone
  28. 2008Rebuild the Relative Strength Index as price-scale bands
  29. 2008Reading Relative Strength Index extremes on one price axis with Bollinger Bands and moving averages
  30. 2011Three-filter confirmation for short-swing futures
  31. 2011Constructing an inverse Fisher stochastic with bands and averages
  32. 2012Constructing a Bollinger Band indicator suite
  33. 2012Stacking price extremes, crossovers, bands, and MACD
  34. 2012Adaptive Bollinger band impulse, trend, and momentum filters
  35. 2013Rescaling stochastic, percent-B, and wave-count parameters
  36. 2014Industry-group quartile pivots as a Bollinger Bands case study
  37. 2014Bollinger Bands as adaptive price envelopes: a 2014 classroom case
  38. 2016Trend-channel entry rules from stacked moving averages
  39. 2016A permission stack for Bollinger, RSI, and the 50-period average
  40. 2017Constructing weighted Bollinger bands and volume averages
  41. 2017Four swing-entry rules that share a timed exit
  42. 2017Two-wave monthly cycles as a regime filter
  43. 2019Constructing exponential-deviation-bands from a midline-average
  44. 2020Critiquing exponential variants of Bollinger Bands
  45. 2020Constructing selectable volatility and moving-average bands
By fieldIndicators and filters682 readingsBy year2017100 readings
All 84 readings tagged Bollinger Bands
Also on Bollinger Bands5 readings
1992Constructing volatility-scaled bands with relative strength index confirmation1992Constructing a weighted-average TRIN10 with Bollinger envelopes1996Constructing Bollinger bands, percent-b, and stochastics1997Asymmetric volatility band construction1998Constructing three-state filters from Bollinger band envelopes