Standard Deviation (StdDev)
Standard Deviation measures the dispersion of price from its mean. Higher values indicate greater volatility. It is the mathematical foundation of Bollinger Bands.
- Family
- Volatility
- Series
- Periods 20
- Best timeframes
- H1 · H4 · D1
- Last updated
- 2026-03-21
TL;DR
- StdDev is a volatility indicator used in technical analysis
- Rising StdDev = increasing volatility. Falling StdDev = decreasing volatility (potential breakout ahead). Spike in StdDev often accompanies trend-starting moves.
- Best timeframes: H1, H4, D1
- Skip to API docs
What is Standard Deviation?
Standard Deviation measures the dispersion of price from its mean. Higher values indicate greater volatility. It is the mathematical foundation of Bollinger Bands.
How StdDev is calculated
StdDev = √(Σ(xi - x̄)² / n)
where xi = price, x̄ = mean price, n = period
Default period: 20How to interpret StdDev
Rising StdDev = increasing volatility. Falling StdDev = decreasing volatility (potential breakout ahead). Spike in StdDev often accompanies trend-starting moves.
Trading strategies using StdDev
Strategy 1: Volatility Breakout
Trade when StdDev spikes from low levels, indicating a new trend starting.
Entry rules
Enter in the direction of the breakout when StdDev rises above its 20-bar average from a low level.
Exit rules
Exit when StdDev begins declining from elevated levels.
Combining StdDev with other indicators
StdDev works best when combined with complementary indicators:
- StdDev + Bollinger Bands: Combine for stronger confluence signals
- StdDev + ATR: Combine for stronger confluence signals
StdDev across different timeframes
StdDev works across all 7 timeframes but performs best on H1, H4, D1 for most trading styles.
Accessing StdDev via the TickAtlas API
GET https://tickatlas.com/v1/indicator
Python example
import requests
url = "https://tickatlas.com/v1/indicator"
headers = {"X-API-Key": "YOUR_API_KEY"}
params = {
"symbol": "EURUSD",
"indicator": "StdDev_20",
"timeframe": "H1"
}
response = requests.get(url, headers=headers, params=params)
data = response.json()
print(data)Sample response
{
"success": true,
"data": {
"symbol": "EURUSD",
"indicator": "StdDev_20",
"timeframe": "H1",
"value": 0.00114,
"updated_at": 1711548000,
"server_time": "2024-03-27T14:00:00+00:00",
"bid": 1.0856,
"ask": 1.0857
}
}Common mistakes to avoid
- Confusing high StdDev with directional bias — volatility has no direction
- Not normalizing StdDev across different price levels when comparing symbols
Frequently asked questions
How does StdDev relate to Bollinger Bands?
Bollinger Bands are built using StdDev. The upper/lower bands are placed at ±2 standard deviations from the SMA. Higher StdDev = wider bands.
Continue learning
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Put StdDev to work in your application.
Sign up with $2.50 of starting credit and query pre-calculated StdDev data across 7 timeframes, from M1 to D1.