Bollinger Bands: 1, 2 or 3 Standard Deviations? Backtest Results

The Bollinger Band dialog has a box called “Deviation” or “Standard Deviations.” Two is the familiar default, but whether 1σ, 2σ or 3σ is best depends first on what you do at the band.

We tested USD/JPY from 0.5σ through 4σ in 0.25 steps, crossed with seven periods from 10 to 50. A lower-band fade, an upper-band fade and a close-based breakout were run on 15-minute, hourly and four-hour bars across 2024, 2025, and the two halves of 2025: 3,780 backtests in all.

The short answer is that 1σ is a defensible starting point for an hourly breakout. From 0.5σ through 1.25σ, all seven periods were profitable in both 2024 and 2025. At 1σ, the seven-period mean was +1,568.8 pips in 2024 and +1,081.9 in 2025. At 1.75σ it was +1,850.2 in 2025 but only +590.2 in 2024.

That does not make 1σ universally optimal. It means that, among these candidates, 1σ made the best compromise between profit, survival across periods and transfer to another year. The fade did not produce a repeatable “best sigma.”

0.5 to 1.25σ1.5 to 4σseven periods; USD/JPY hourly breakout

What Bollinger Bands sigma changes

Let SMA(n) be the simple moving average of the last n closes, SD(n) their standard deviation and k the deviation setting. The bands are:

Upper = SMA(n) + k × SD(n)

Lower = SMA(n) − k × SD(n)

The 2 in the settings dialog does not mean 2%. It multiplies the rolling standard deviation by two. Raising sigma pushes both bands away from the mean, producing fewer touches and fewer close-based breaks. Raising period also tends to reduce frequency because the centre line reacts more slowly.

The often-quoted 68%, 95% and 99.7% figures for 1σ, 2σ and 3σ describe a normal distribution of independent observations. A market has serial dependence, trends and jumps, so those percentages are not market signal frequencies.

closes finishing insideperiod 20; 6,226 USD/JPY H1 bars in 2025

On 6,226 hourly USD/JPY bars in 2025, using period 20, 45.0% of closes finished inside 1σ, 87.1% inside 2σ and 99.1% inside 3σ. That leaves 12.9% outside 2σ. Merely reaching 2σ does not establish that price is abnormal or due to reverse.

The settings dialog

For the conventional 20-period, 2σ display in MT4 or MT5, the inputs are below. TradingView and Formiq expose the corresponding period and deviation fields.

Formiq's backtester adds a trigger choice.

The same 20 and 2σ can give opposite results when a touch is faded and a close outside is followed. The trading direction has to be fixed before sigma can be compared.

How this was measured

The fade's opposite band stays fixed at 1σ so the experiment changes the entry sigma only. Moving the entry and exit together would not reveal which one caused the result.

Which sigma works best?

On the hourly chart the 0.5σ to 1.25σ band was the steadiest. Each row below averages its seven periods. “Positive both” counts the periods that made money in both 2024 and 2025.

All seven periods survived both years from 0.5σ through 1.25σ. At 1σ, the means were +1,568.8 pips in 2024 and +1,081.9 in 2025. Two sigma was also viable, with six of seven periods positive in both years, but its result depended more on period.

The apparent return to four survivors from 3.5σ upward needs the trade column beside it. Those settings averaged 6.3, 4.1 and 2.3 trades in 2025. A few successful outliers are not the same as a stable setting.

The whole 105-setting breakout grid changed with timeframe.

Hourly bars retained 67 settings in both years. Four-hour bars went from 84 winners in 2024 to 32 in 2025, which is why the answer here is explicitly an hourly one.

Are 2 standard deviations any good?

At period 20 alone, 1.75σ beat both 1σ and 2σ in both years. Fixing the period makes the frequency change easier to see.

Across all seven periods in 2024, however, 1.75σ averaged +590.2 pips versus +1,568.8 at 1σ. A result after fixing one period is a different comparison from a result averaged across periods.

Which sigma for mean reversion?

No sigma was stable for the fade. The 105 hourly settings point in a different direction when the band is faded.

Widening the entry often made the fade-long loss smaller. Averaged over seven periods, 1σ made −811.6 pips in 2025 and −111.6 in 2024. At 2.75σ the figures were +230.2 and −45.3; at 3σ, +35.6 and −12.7.

The fade-long result at 2.75σ was +230.2 pips in 2025 and −45.3 in 2024; at 3σ it was +35.6 and −12.7. The short fade retained just one of 105 settings in both years. A wider band may simply trade less and therefore lose less; it did not establish a repeatable mean-reversion setting.

Does one year's best sigma hold?

The single-year maximum shrank the next year, while 1σ held in both. Choosing sigma by the largest 2025 mean selects 1.75σ at +1,850.2 pips. In 2024 it made +590.2. The 1σ setting made +1,568.8 in 2024 and +1,081.9 in 2025.

Optimizing period and sigma together is less stable still. Period 10 and 1.75σ made +2,753.0 pips in 2025 but +686.0 in 2024. Period 25 and 2.25σ made +2,793.5 in 2024 but +231.3 in 2025. That is why the conclusion favors several nearby settings that stayed positive in both years over one maximum cell.

Can win rate choose sigma?

No. Averaged over all 105 hourly settings in 2025, the fade long won 61.9%, the fade short 61.2% and the breakout 41.0%.

The fade is right more often but loses more when wrong. The breakout's average winner is about twice its average loser. Looking only for the sigma with the highest hit rate discards that payoff shape.

Filters, exits and costs

We added common filters to the period 20 and 1σ breakout used as the robust baseline.

None of the ADX thresholds beat the baseline in both years. London and New York hours improved it slightly in both, from +1,052.5 to +1,073.5 in 2025 and +2,071.7 to +2,154.3 in 2024, but that session result needs more pairs and years before it becomes a setting recommendation.

Fixed stops and targets are executable levels measured from the filled entry. When reached, they fill at the configured distance without another exit-side adjustment being deducted from that level.

Fixed stops and targets improved 2025 at the cost of 2024. None beat the plain rule in both years.

With spread varied on the 2025 period 20 and 1σ breakout, net profit moved from +1,135.6 pips at zero to +1,052.5 at 0.3, +858.6 at 1, +581.6 at 2 and +304.6 at 3 pips. Its simple break-even spread was about 4.10 pips. One sigma trades often, so low cost is part of the setting.

Which Bollinger Bands period works best? compares lookbacks from 5 through 200 and tests whether the best bar count changes with timeframe. The broader comparison between fading and following the bands is in 315 Bollinger Band backtests. RSI periods and 30/70 levels also show why a higher fade win rate need not produce more profit. MA disparity settings put the band at a percentage of price rather than a standard deviation, while backtesting without code shows how to rebuild the condition on your own pair.

Notes

• One pair, USD/JPY, and two independent calendar years. Nothing here guarantees the same order on other pairs or regimes
• Picking a winner from a period-and-sigma grid creates a multiple-comparison uplift. The other year checks it, but is not an untouched future sample
• Three sigma and wider settings have small samples. A 4σ mean of 2.3 trades cannot be compared with 260.4 trades at 1σ at equal confidence
• Touch rules use highs and lows; breakouts use closes. Counting wick breaks as signals would produce a different test
• Fills are at bar closes and spread is fixed. Live fills and changing spreads are not reproduced
• The fade exit stays at the opposite 1σ band to isolate entry sigma. A study that optimizes the exit as well answers a different question