Donchian Channels vs Standard Deviation
Donchian channels plot the highest high and lowest low over a lookback, so both lines are prices that genuinely traded. Standard deviation measures how far prices have typically sat from their own average, which is a statistic rather than a level and is the basis of bands drawn around a moving average.
Both of these are ways of putting a boundary around recent price. One takes the boundary from what actually happened; the other computes it from a formula that carries an assumption most people never examine.
What each one is
Donchian channels draw the highest high and the lowest low over a lookback. Both lines are prices that traded, and the channel is simply the range. Donchian channels covers it.
Standard deviation measures the typical distance of prices from their own mean. It is a statistic, not a level, and it is what bands around a moving average are built from. Standard deviation covers it, and Bollinger Bands covers the most common application.
One is observed and the other is computed. Whereas a donchian line marks a price somebody paid, a standard-deviation band marks a distance derived from a formula, and no trade need ever have happened there.
Where they differ
Whether the boundary is a real price. A donchian edge is a level the market reached. A band edge is an arithmetic result, which matters because a level other participants can see is partly self-fulfilling and a computed one is not.
What assumption is being made. Standard deviation is most meaningful when the data is roughly bell-shaped, and price returns are not — the extremes are more common than the mathematics predicts. So a two-deviation band that should contain the great majority of observations contains fewer, and the ones it misses are the largest moves.
How each responds to a single event. One enormous bar sets a donchian edge and holds it for the whole lookback, so the channel remembers a single day for as long as it is in the window. Standard deviation absorbs that bar into an average, so it widens rather than jumping.
How each behaves when nothing happens. A quiet stretch leaves donchian lines frozen at old extremes while standard deviation contracts steadily — the second is a live reading of current conditions, the first is a record of the recent past.
Where they agree
Both are descriptions of recent range, and neither claims to know where price goes next.
Both are computed from price alone, with no volume and no second input.
Both cost a round trip when acted on — 0.0098 on this site’s shared series, about 2% of the median bar range of 0.493.
And both are ruined by the same condition. Direction runs here average 2.01 bars with a longest of 11, which produces edges that are touched and rejected repeatedly.
Which one to use
Use donchian channels when you are trading breakouts. The edge is a real price, other participants can see the same level, and on this site’s shared series 85% of 39 twenty-bar breakouts continued and 11 of 11 fifty-five-bar breakouts did — small samples pointing the same way.
Use standard deviation when you want to know how volatile things are now. It contracts and expands continuously, which a channel frozen at an old extreme does not — so as a measure of current conditions it is the better of the two.
Use donchian when the lookback is long. A fifty-five-bar high is a meaningful event; a fifty-five-bar standard deviation is a slow-moving statistic.
And when you use bands, do not treat the outer edge as a limit. The distribution assumption behind it does not hold, and the moves that exceed it are the ones that matter.
Why the distribution assumption matters
Because the tails are fatter than the formula expects. On this series the median bar range is 0.493, the ninetieth percentile 1.101 and the largest 2.338 — more than four times the median. A measure built for a bell-shaped distribution treats that last bar as far rarer than it is.
And because a quiet period tightens the bands immediately before the move that ends it. Contraction is read as a signal, and it is also the state in which the band is least able to contain what follows.
The original data
Of the 24,971 unique videos in the search corpus, no title compares these two directly. Donchian channels appear in 59 titles at a median of 10,071 views across 54 channels. Standard deviation appears in exactly 1, at 30,395 views.
One video, in a corpus of 24,971. Standard deviation is the statistic underneath one of the most popular indicators in existence and almost nobody teaches it directly — the bands are covered constantly and the measure they are built from is covered once, which is a good description of how the tool is usually understood.
On the chart above the channel edge is a level and the band edge is a statement about rarity — and the rarity claim is the one resting on an assumption the data does not support.
When it fails
The characteristic failure is treating a two-deviation band as a boundary price should respect. The figure comes from a distribution model in which such excursions are unusual, and price returns have substantially fatter tails than that model — so the outer band is exceeded more often than the mathematics implies, and specifically during the large moves that do the most damage. A trader fading the band is taking a position sized by an assumption that fails exactly when the position is largest, which is why the strategy can work for long stretches and then lose more than all of it.
A second failure is treating a donchian edge as current information. It can be a single old bar held in place by the lookback rather than anything happening now.
A third is using a short donchian lookback for breakouts, where 2.01-bar direction runs clear a twenty-bar high routinely.
A fourth is reading band contraction as a directional signal. It says volatility is low and nothing about which way the resolution goes.
And a fifth is stacking both on one chart as confirmation, when both are computed from the same prices and neither adds an input.
Related
Donchian channels covers the observed high-low range. Standard deviation covers the dispersion statistic. And Bollinger Bands covers the most common way it is drawn on a chart.
The honest problem with standard deviation on price is that it borrows a tool built for a bell-shaped distribution and applies it to something with much fatter tails. The two-deviation band that should contain most observations contains fewer than the mathematics promises, and the misses are the days that matter.
— Michael Whitman
This page is educational, not financial advice. Test every idea on your own charts before risking money.