Dynamic Standard Deviations for NinjaTrader 8
Projects volatility-based levels from session opens across multiple timeframes. Calculates how far price typically moves using historical data, then draws those statistical zones on your chart automatically.
See It in Action
Watch how the Dynamic Standard Deviations indicator calculates and displays volatility levels.
Volatility Levels That Adapt to Current Conditions
Standard deviation tells you how far price typically moves from a reference point. This indicator calculates that for each timeframe and projects those zones from each session's open.
Three Timeframes, One Chart
Daily levels project from the session open at midnight. 4-hour levels recalculate every four hours (02:00, 06:00, 10:00, 14:00, 18:00, 22:00 ET). Hourly levels update each hour. Toggle any timeframe on or off.
Rolling Calculation Window
At midnight each day, the indicator analyzes the previous 90 days of price data (configurable from 30-365 days) to calculate fresh standard deviations. This keeps your levels relevant to current market volatility rather than outdated conditions.
Multiple SD Bands
Display 0.5, 1.0, 1.5, and 2.0 standard deviation levels both above and below the session open. Each band represents a probability zone—1.0 SD captures about 68% of typical moves, 2.0 SD captures about 95%.
Time-Specific Volatility
The indicator calculates separate standard deviations for each 4-hour period and each hour of the day. The 10:00-14:00 ET session typically has different volatility than the overnight 22:00-02:00 session, and this is reflected in the levels.
Common Trading Applications
Standard deviation levels provide statistical reference points. Here are the typical ways traders incorporate them into their analysis.
Mean Reversion at Extremes
When price reaches the 1.5 or 2.0 SD bands, it's statistically extended. Some traders look to fade these moves back toward the mean (session open or 1.0 SD level). The probability math suggests extended moves tend to revert.
- Wait for price to reach outer bands (1.5 SD or 2.0 SD)
- Look for reversal confirmation before entry
- Target the 1.0 SD level or session open
Breakout Continuation
When price breaks through one SD level with momentum, it often continues to the next. The levels act as stepping stones—breaking the 0.5 SD suggests the 1.0 SD is in play, breaking 1.0 SD puts 1.5 SD on the radar.
- Entry after price claims a SD level with momentum
- Stop just inside the previous SD level
- Target the next SD level
Time-Based Position Sizing
Different times of day have different volatility patterns. The hourly and 4-hour bands reflect this. Some traders use wider bands during high-volatility periods to size positions smaller, and tighter bands during quiet periods to size larger.
- Compare band width across different sessions
- Tighter bands = lower volatility expectation
- Adjust position size based on expected range
On Real Futures Charts
See how the Dynamic Standard Deviations indicator displays volatility levels across different market conditions.
Indicator Settings
Customize the indicator to match your trading preferences.
| Setting | Default | Description |
|---|---|---|
| Lookback Days | 90 | Number of days to look back for standard deviation calculations |
| Historic Periods to Show | 24 | Number of periods to display per timeframe (1-168) |
| Show H1 Levels | True | Show hourly standard deviation levels |
| Show H4 Levels | True | Show 4-hourly standard deviation levels |
| Show D1 Levels | True | Show daily standard deviation levels |
| Show 0.5 SD | On | Toggle 0.5 standard deviation bands |
| Show 1.0 SD | On | Toggle 1.0 standard deviation bands |
| Show 1.5 SD | On | Toggle 1.5 standard deviation bands |
| Show 2.0 SD | On | Toggle 2.0 standard deviation bands |
| H1 Line Color | Yellow | Color for hourly SD lines |
| H1 Label Color | Yellow | Color for hourly SD labels |
| H4 Line Color | DarkOrange | Color for 4-hour SD lines |
| H4 Label Color | DarkOrange | Color for 4-hour SD labels |
| D1 Line Color | Crimson | Color for daily SD lines |
| D1 Label Color | Crimson | Color for daily SD labels |
Number of days to look back for standard deviation calculations
Number of periods to display per timeframe (1-168)
Show hourly standard deviation levels
Show 4-hourly standard deviation levels
Show daily standard deviation levels
Toggle 0.5 standard deviation bands
Toggle 1.0 standard deviation bands
Toggle 1.5 standard deviation bands
Toggle 2.0 standard deviation bands
Color for hourly SD lines
Color for hourly SD labels
Color for 4-hour SD lines
Color for 4-hour SD labels
Color for daily SD lines
Color for daily SD labels
What Users Say
Trusted by futures traders worldwide
The multi-timeframe thing is what makes this work. I can see daily context while trading hourly setups. When they line up, those are my best trades hands down.
Finally a standard deviation indicator that actually adapts. That 90-day rolling window keeps the levels relevant without freaking out from short-term spikes.
I fade the 2.0 SD bands on NQ all the time. When price hits those extremes it's stretched way too far. Doesn't work every time but the win rate is solid.
That 4-hour session breakdown is genius. ES and NQ move totally different during Asia vs New York. This actually shows you the numbers.
Super clean and you can turn stuff on and off. I only show daily and 4-hour to keep my chart simple. Color coding makes it easy to tell them apart.
Ditched my Bollinger Bands for this. These session-anchored levels don't move during the day which makes planning way easier.
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Common Questions
- Standard deviation measures how much price typically varies from an average. In this indicator, we calculate how far price typically moves from each session\'s open based on the last 90 days of data. One standard deviation (1.0 SD) captures about 68% of typical moves, meaning price stays within those bounds roughly two-thirds of the time. Two standard deviations (2.0 SD) captures about 95% of moves.
- At midnight each day, the indicator looks back at the previous 90 days (or whatever you configure between 30-365 days) and calculates fresh standard deviations. This means your levels adapt to changing market volatility over time. If volatility increases, your bands widen. If it decreases, they contract. The rolling window balances statistical significance with market relevance.
- Market volatility varies throughout the trading day. The overnight Asia session (22:00-02:00 ET) typically has lower volatility than the New York morning (10:00-14:00 ET). Using a single daily SD would create misleading levels—too wide for quiet periods, too narrow for volatile ones. The indicator calculates separate SDs for six 4-hour periods and 23 individual hours to reflect these patterns.
- Bollinger Bands anchor to a moving average, so the bands move as price moves during the session. This indicator anchors to the session open price, so the levels are fixed once the session starts. This makes it easier to set alerts and plan trades around specific levels. We also calculate separate SDs for different times of day, which Bollinger Bands don\'t do.
- Any liquid futures market with consistent trading volume. It works particularly well on index futures (ES, NQ, YM, RTY) where institutional participation creates reliable volatility patterns. Energy markets (CL, NG) also work well. The key requirement is sufficient volume to generate meaningful volatility data over the calculation window.
Statistical Levels, Automatically Calculated
Stop guessing where price might find support or resistance. Let the math tell you where price typically turns based on historical volatility patterns.
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Testimonials appearing on this website may not be representative of other clients or customers and is not a guarantee of future performance or success.
Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown; in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk of actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all which can adversely affect trading results.