Smoothed Moving Average (SMMA) in TradingView: Formula, Settings, and Uses

The Smoothed Moving Average (SMMA) is a slow, trend-following moving average that uses all available historical data instead of dropping the oldest bar like an SMA does. In TradingView, the built-in SMMA indicator defaults to a 9-period length applied to the close price. Its calculation is mathematically identical to Wilder's smoothing — the same technique used inside RSI, ATR, and the Alligator indicator — and in Pine Script it is available as ta.rma(src, length). Use SMMA when you want a calmer, slower trend filter; avoid treating it as a fast entry signal, because its reduced noise comes at the cost of meaningful lag.

Key Takeaways

• SMMA is Wilder's smoothing. It uses a recursive formula with a smoothing factor of 1 / length, the same math behind RSI and ATR.
• Among the common moving average types, SMMA is the slowest and smoothest for the same nominal length, which reduces whipsaws in trending conditions but adds more lag than SMA or EMA.
• A 10-period SMMA behaves roughly like a 19-period EMA, because SMMA with length N is equivalent to an EMA with period 2N − 1.
• TradingView's built-in SMMA defaults to length 9 on close; longer periods smooth more, shorter periods react faster.
• Best used as a trend filter or dynamic support/resistance level, not as a standalone entry signal in choppy, range-bound markets.

What Is the Smoothed Moving Average (SMMA)?

A moving average summarizes price over a window, but different types assign weight differently. The Simple Moving Average (SMA) gives every bar equal weight and drops the oldest bar completely when a new one arrives. The Exponential Moving Average (EMA) weights recent bars much more heavily so it turns quickly. The Smoothed Moving Average sits at the calmer end of this spectrum.

Two properties define SMMA:

1. Older prices are never fully removed. Once a price enters the calculation, its influence decays over time rather than dropping to zero on a fixed schedule. TradingView's own definition states that SMMA uses a longer time period and is designed to make older and recent prices carry more equal weight.
2. The smoothing factor is small. At 1 / length, it adjusts very gradually, producing a line that filters most intrabar noise.

The practical outcome is a clean, slow-moving trend line. This is exactly why classic indicators like Wilder's RSI and Bill Williams' Alligator were built on it — stability matters more to their logic than speed.

How TradingView Calculates the SMMA

SMMA is seeded with a simple average, then updated recursively. The standard steps are:

1. Compute the SMA of the first N bars to get the starting SMMA value.
2. For each new bar, apply the recursive formula below.

The SMMA formula:

Seed:        SMMA₁ = SMA(close, N)
Recursive:   SMMA(i) = [ SMMA(i−1) × (N − 1) + close(i) ] / N
Equivalent:  SMMA(i) = SMMA(i−1) + [ close(i) − SMMA(i−1) ] / N

This is identical to Wilder's smoothing (also called RMA or Relative Moving Average). In Pine Script v6, ta.rma(src, length) computes it directly using alpha = 1 / length. Several classic indicators use Wilder-style smoothing, including RSI, ATR, and common ADX implementations.

Pine Script example:

//@version=6
indicator("SMMA / Wilder Smoothing", overlay=true)
length = input.int(9, title="Length", minval=1)
smma = ta.rma(close, length)
plot(smma, title="SMMA", color=color.orange)

This snippet reproduces the built-in SMMA line. You can change the close source or the length to match your use case.

The 2N − 1 EMA Equivalence

SMMA and EMA share the same recursive form but use different alphas. SMMA's alpha is 1/N; an EMA's alpha is 2/(P+1). Setting them equal gives P = 2N − 1. TradingView's Help Center confirms you can relate a smoothed period to an EMA period via this relationship.

If you want an SMMA feel from an EMA indicator, roughly double the length and subtract one.

How to Add the SMMA Indicator in TradingView

The SMMA is a built-in indicator, so you do not need a community script to use it. Steps below reflect the current TradingView interface; menu labels may shift as the product is updated.

1. Open a chart. Go to TradingView, open Supercharts, and pick a symbol and timeframe.
2. Open the Indicators menu. Click Indicators at the top of the chart toolbar.
3. Search for it. Type Smoothed Moving Average in the search box. The built-in version appears under Technical indicators (look for the TradingView logo rather than a community author name).
4. Add it. Click the result — the SMMA line plots on your chart immediately.
5. Adjust the settings. Hover the indicator name on the chart, click the gear (⚙) icon, and change Length (default 9), Source (default close), or Offset. You can also set alerts from the three-dot menu.

Default Settings at a Glance

SMMA vs SMA vs EMA vs WMA

Choosing the right average is mostly about the trade-off between responsiveness and noise. The table below summarizes how SMMA fits in relative to common alternatives.

Read this as a sliding scale: moving from WMA/EMA toward SMMA, you trade speed for stability. "Fewer whipsaws" in trending conditions comes at the cost of later entries and exits — test on your specific asset and timeframe before relying on any setting.

How Traders Commonly Use SMMA

1. Trend Filter

Use one long-period SMMA as a regime filter. Price above a rising SMMA suggests a bullish environment; price below a falling SMMA suggests a bearish one. A 50- or 200-period SMMA on the daily chart is a common application. Because the line is slow, brief pullbacks rarely flip the bias — but verify on historical data for each asset you trade before treating it as a rule.

2. SMMA Crossover

Plot a fast SMMA (e.g., 5–9) and a slow SMMA (e.g., 20–50). A potential long signal appears when the fast line crosses above the slow line; a short signal on the reverse cross. Crossovers are smoother than EMA crossovers and tend to produce fewer signals — this reduces whipsaws in trending markets but delays entries. Always back-test crossover thresholds on your specific market and timeframe.

3. Dynamic Support and Resistance

In a clean trend, a 20- or 50-period SMMA may act as a moving floor (uptrend) or ceiling (downtrend). Some traders watch for price to pull back to the SMMA and resume as a potential lower-risk entry area. The smoothing creates a wider "support zone" than a fast EMA would. No moving average level is a guaranteed support; always use additional confluence (volume, momentum, structure) before acting.

SMMA Use Case Decision Table

A classic multi-SMMA setup is Bill Williams' Alligator, which stacks three SMMAs of the median price (hl2): the Jaw (13-period, shifted 8 bars), Teeth (8-period, shifted 5 bars), and Lips (5-period, shifted 3 bars). When the three lines fan apart in sequence, the Alligator is trending; when they braid together, the market is ranging and crossover signals are less reliable.

Best SMMA Settings by Use Case

TradingView's built-in default is length 9 on close. For most higher-timeframe trend filtering, longer periods (50, 200) are more meaningful. Always test any setting on historical data before using it in a live trading decision.

SMMA Setup Reading Checklist

Before acting on an SMMA signal, work through these five questions:

• Trend direction — Is the SMMA line rising, falling, or flat?
• Slope — Is the slope steepening (momentum building) or flattening (momentum waning)?
• Distance from price — Is price close to the SMMA (potential S/R test) or far away (extended)?
• Confirmation — Does a momentum indicator (RSI, MACD) or volume support the directional bias?
• Invalidation level — At what price would the SMMA bias clearly break (e.g., a candle close on the wrong side)?

Common Mistakes to Avoid

• Treating SMMA as a leading signal. It is a lagging indicator by design. Use it to confirm, not to predict tops and bottoms.
• Using it alone in range-bound markets. SMMA flattens during sideways price action, and crossovers in a choppy market can produce losses. Pair with a volatility or momentum filter (ATR, RSI) or wait for a clear trend.
• Confusing it with SMA. They share a similar name but behave differently. SMMA retains all historical data with decaying weight; SMA drops the oldest bar. Mixing them up changes backtest results.
• Expecting EMA-like speed from a 9-period SMMA. A 9-period SMMA reacts roughly like a 17-period EMA. If you need fast signals, use a shorter SMMA length or switch to EMA.
• Ignoring the seed value on short histories. The first SMMA value is the SMA of the first N bars. On charts with limited history, give it enough bars to stabilize before reading signals.
• Assuming repaint-free closed bars are always stable. SMMA, like any moving average, does not repaint closed historical bars unless the source data or settings change. The live (open) bar's value updates tick-by-tick until the bar closes, which is normal behaviour.

FAQ

What is the Smoothed Moving Average (SMMA)?

The Smoothed Moving Average is a recursive moving average that uses all available historical data and applies a smoothing factor of 1 / length. Older prices are never fully removed — their influence decays gradually. This produces a slower, steadier line compared to SMA or EMA of the same nominal length, making it useful for filtering short-term noise in trend-following strategies.

How do I add the Smoothed Moving Average in TradingView?

Open a chart, click Indicators, search for Smoothed Moving Average, and click the built-in result (TradingView logo). It plots on the chart with default settings of length 9 applied to close. Click the gear icon to change the length, source, or offset.

What is the SMMA formula?

Seed the first value with SMA(close, N), then apply: SMMA(i) = [SMMA(i−1) × (N − 1) + close(i)] / N. This is identical to Wilder's smoothing and is computed in Pine Script with ta.rma(src, length).

Is SMMA the same as RMA or Wilder's smoothing?

Yes. SMMA, RMA (Relative Moving Average), and Wilder's smoothing are the same calculation with alpha = 1 / length. In Pine Script v6, ta.rma(src, length) computes it. The TradingView Pine Script Reference documents ta.rma() as using this exact smoothing method.

Is SMMA the same as EMA?

No. Both use a recursive form, but SMMA's alpha is 1/N while EMA's alpha is 2/(P+1). A 10-period SMMA behaves roughly like a 19-period EMA (2 × 10 − 1 = 19). SMMA is slower and smoother than an EMA of the same stated period.

What is the best SMMA length in TradingView?

There is no universally best length — it depends on your timeframe and strategy. TradingView's default is 9. For trend filtering on the daily chart, 50 or 200 are common. For shorter swing setups, 20–21 works well. Always test the specific length on the asset and timeframe you plan to trade.

Is SMMA better than SMA?

Neither is universally better. SMMA is slower and smoother because it retains older data with decaying weight, while SMA gives equal weight to all bars in its window and drops the oldest. SMMA tends to produce fewer whipsaws in strong trends but lags more when the trend reverses. SMA is simpler and easier to reason about for backtesting fixed lookback windows.

What is the default SMMA period in TradingView?

The built-in Smoothed Moving Average indicator defaults to a length of 9 applied to the close price.

Can I use SMMA for scalping?

SMMA can be applied on short timeframes, but its lag makes it less naturally suited to fast scalping. EMA or WMA typically respond faster to price changes. If you use SMMA for scalping, a short length (5–7) helps, but verify on historical tick data that the signals suit your execution speed.

Does SMMA repaint?

No. SMMA does not repaint on closed historical bars (unless you change the source or settings). The current bar's value updates continuously until the bar closes, which is standard behaviour for any real-time moving average indicator.

Next Steps

1. Add the built-in SMMA to a daily chart at length 50 and observe how price interacts with it over several months of history before using it in a live decision.
2. Stack a fast/slow SMMA pair (e.g., 9 and 21) and log every crossover for one symbol — count how many were profitable in hindsight to calibrate your expectations.
3. Compare SMMA to an EMA of period 2N − 1 on the same chart to build intuition for the equivalence; they should track almost identically.
4. Pair SMMA with a momentum filter such as RSI or a volatility filter such as ATR to avoid acting on crossovers during flat, range-bound markets.
5. Use ChartMini (https://chartmini.com) as a lightweight chart-practice reference to compare how different SMMA lengths change trend visibility across timeframes before applying any setup in live markets.

Sources

• TradingView Help Center — Smoothed Moving Average (definition, default settings, Period = 2*n − 1 relationship): https://www.tradingview.com/support/solutions/43000591343-smoothed-moving-average/
• TradingView Help Center — Moving Averages (built-in indicator overview): https://www.tradingview.com/support/solutions/43000502589-moving-averages/
• TradingView Pine Script Reference v6 — ta.rma() (Wilder's smoothing, alpha = 1 / length): https://www.tradingview.com/pine-script-reference/v6/#fun_ta.rma
• TradingView — Alligator indicator scripts and documentation: https://www.tradingview.com/scripts/alligator/
• Investopedia — Exploring the Williams Alligator Indicator (Jaw/Teeth/Lips parameters): https://www.investopedia.com/articles/trading/072115/exploring-williams-alligator-indicator.asp
• LuxAlgo — Smoothed Moving Average Indicator: Less Choppy Trend Line: https://www.luxalgo.com/blog/smoothed-moving-average-indicator-less-choppy-trend-line/
• Quantified Strategies — Smoothed Moving Average (Wilder's) Trading Strategy: https://www.quantifiedstrategies.com/smoothed-moving-average/

Trading involves risk. Moving averages are analytical tools, not guarantees of future performance. Always test any setup on historical data, and size positions according to your own risk tolerance.