Smoothed Moving Average (SMMA) | RizeTrade

What Is a Smoothed Moving Average (SMMA)?

SMMA Definition: What Does It Measure?

The Smoothed Moving Average (SMMA), also called Wilder's Smoothed Moving Average, is a moving average built to iron out price swings without completely ignoring the past. It keeps all historical prices in the math, but the older they are, the less they matter.

The result is a trend line that’s cleaner than an SMA, but not as jumpy as a fast EMA.

How Does SMMA Reduce Noise in Price Charts?

Most traders use SMMA to cut through short-term chop and see the real direction. Because it updates using a recursive calculation, the line doesn’t kink every time you get a one-candle spike.

That’s why it tends to hold up better in messy volatility—especially on FX pairs like EUR/USD or crypto like BTC/USD where fake-outs are common.

SMMA vs SMA vs EMA vs WMA: What’s the Difference?

Here’s the practical difference in how each one “treats” price:

• Simple Moving Average (SMA): Every close in the lookback gets the same weight, so it’s clean but can lag hard.

• Exponential Moving Average (EMA): Heavily weights the most recent candles, so it reacts fast but whipsaws more.

• Weighted Moving Average (WMA): Linear weighting toward the newest candles, usually more responsive than SMA.

• SMMA: Smooths recursively, so you get a steady line that still adapts as price trends.

Who Created SMMA and Why?

Wilder’s smoothing approach filled a gap between “too slow to be useful” and “too reactive to trust.” It’s the same thinking that made Wilder-style tools popular across commodities, equities, and later forex and crypto—trend clarity first, less attention to every little wiggle.

How Is SMMA Used in Trading Platforms Today?

Most platforms like TradingView and MetaTrader 4/5 ship SMMA out of the box. It’s commonly used for trend confirmation, dynamic support/resistance, and crossover systems in discretionary trading and algo models.

As noted: "The smoothed moving average is smoother than SMA and similar to but slower than EMA" [citation]. That “slower than EMA” part is exactly why swing traders like it—it filters noise without turning into a lagging brick.

How to Use SMMA in Trading (Signals and Strategies)

SMMA Trading Signals: Buy, Sell, and Crossovers

SMMA signals are straightforward, but they work best when you treat them as trend filters, not magic triggers:

• Buy Signal: Price closes back above the SMMA and holds, ideally after a pullback in an uptrend.

• Sell Signal: Price closes below the SMMA and can’t reclaim it, usually after a bounce fails in a downtrend.

• Crossover Signals: A fast SMMA crossing a slow SMMA can mark a regime shift, especially on higher timeframes.

SMMA Golden Cross and Death Cross: What Do They Signal?

A golden cross is when the shorter-period SMMA crosses above the longer-period SMMA. It’s a bullish trend cue, and on something like the S&P 500 or a large-cap stock basket it can pull in systematic flows.

A death cross is the opposite and often shows up when rallies start failing and lower highs stack up. These golden cross and death cross strategies work best in clean trends; in a range, they’ll chew you up unless you add filters.

How SMMA Acts as Dynamic Support and Resistance

In an uptrend, SMMA often acts like dynamic support—price pulls back into it, buyers step in, and the trend continues. In a downtrend, it flips to dynamic resistance.

Running a “stack” (like 20/50/200 SMMAs) can help you spot confluence zones where price is more likely to react.

Best Indicators to Combine with SMMA

SMMA gets stronger when you pair it with tools that answer different questions:

1. SMMA + RSI: SMMA sets the trend bias; RSI helps time pullbacks (overbought/oversold or the 50-line).

2. SMMA + MACD: SMMA confirms direction; MACD helps confirm momentum shifts.

3. SMMA + Volume: Volume tells you if the move has real participation or it’s just a low-liquidity drift.

How to Build and Backtest an SMMA Strategy

SMMA systems work when the rules are tight: define the trend filter, define the trigger, define the exit. Then backtest it on the instrument you actually trade—BTC behaves differently than USD/JPY, and both behave differently than a single-name stock like NVIDIA.

Reference: TradingView SMMA Crossover Strategy

Best SMMA Settings for Trending, Ranging, and Volatile Markets

SMMA in Trends vs Ranges: When Does It Work Best?

SMMA shines when the market is actually trending. Higher highs and higher lows? It keeps you on the right side and stops you from panicking out on every pullback.

In a range, it’s a different story—price crosses back and forth and the line becomes a whipsaw machine. When you see compression, overlapping candles, and no follow-through, you either widen filters or stop using SMMA as a trigger and use it only as a soft bias.

How to Use SMMA During High Volatility

SMMA helps you ignore small shakes, but it won’t protect you from real volatility expansion. When ATR jumps or you start seeing long wicks, stops need more air. Otherwise you’ll get clipped and watch price resume without you.

SMMA Multi-Indicator System (RSI, MACD, Volume)

Buy Setup:

1. Price holds above the 200-period SMMA (macro uptrend filter).

2. MACD prints a bullish crossover (momentum turning).

3. RSI pushes out of oversold or holds above 50 (strength stays bid).

4. Volume expands (move has participation, not just a thin grind).

Sell Setup:

1. Price loses the 200-period SMMA (macro downtrend filter).

2. MACD prints a bearish crossover (momentum rolling over).

3. RSI exits overbought or slips below 50 (weakness taking control).

4. Volume expands (selling pressure is real).

SMMA Risk Management: Stops, Position Size, and ATR

For longs, stops usually sit below the last swing low or just under the SMMA if you’re trading a pullback-to-average setup. For shorts, it’s the mirror—above the swing high or above the SMMA.

When volatility spikes, cut size or widen stops, but don’t do both unless your risk model can handle it.

Does SMMA Work for Stocks, Forex, and Crypto?

SMMA works on stocks, forex, and crypto, but the settings shouldn’t be copy-pasted. FX intraday traders often tighten periods to match session flow, while crypto traders usually step up in timeframe because the noise is constant.

Equities still respect the “200-period” crowd effect, but you’ll often get better results tuning by sector (tech vs energy) and liquidity profile.

For more on stacking trend + momentum tools, see high-probability setups for forex traders.

SMMA Pros and Cons: Is It a Good Moving Average?

SMMA Benefits for Traders

• Strong noise reduction, so the chart reads cleaner and trend is easier to hold.

• Solid trend confirmation for swing and position trading.

• Fewer false flips than fast averages in volatile conditions.

• Smooth line makes it easier to manage trades (trail stops, stay in the move).

• Works well as a bias filter across forex, crypto, and equities.

SMMA Drawbacks and Common Mistakes

• It’s still a lagging tool, so it can be late on sharp reversals.

• Choppy ranges cause repeated cross signals and whipsaws.

• Not great for ultra-fast execution styles where you need immediate reaction.

• Early entries are usually better with EMA/price action; SMMA is better for confirmation.

• Works best when combined with momentum, structure, or volume confirmation.

SMMA Characteristics: Smoothness vs Lag in Trend Trading

How SMMA Smooths Price and Filters Noise

SMMA is built for noise control. It leans on recent price, but the recursive update keeps the line from snapping around. That makes it useful when you’re trying to avoid getting baited by one or two candles of volatility.

You still get trend structure, just with fewer false flips than a fast EMA.

Does SMMA Lag More Than EMA?

There’s no free lunch: SMMA will lag more than EMA, but it usually lags less than a comparable SMA. For swing trading, that’s often the sweet spot—less chop, fewer whipsaws, and still quick enough to stay aligned with the move.

For pure day trading or scalping, it can be a touch slow, especially when the market snaps from risk-on to risk-off.

How Reliable Is SMMA for Trend Confirmation?

SMMA tends to ignore sudden one-off spikes but follows sustained pressure. So if price is grinding higher, the line will catch up and hold.

If you get a sharp reversal, it won’t instantly flip, which is good for filtering fake-outs but can cost you early entries. That’s why a lot of traders use it more for confirmation and trade management than for “first signal.”

SMMA to EMA Equivalence: How to Match Periods

A 20-period SMMA is roughly as smooth as a 39-period EMA, which gives you a quick way to translate settings across systems. TradingView documents this equivalence in their official support documentation.

How Do You Calculate a Smoothed Moving Average (SMMA)?

SMMA Formula: How the Calculation Works

SMMA is basically a two-step process: you seed it with a normal average, then you keep updating it using the prior SMMA value. That’s what gives it the smooth, rolling behavior instead of constant resets like an SMA window.

SMMA Mathematical Formula

First SMMA: SMMA(1) = Sum of closing prices over N periods / N

Subsequent SMMA: SMMA(i) = [SMMA(i-1) × (N-1) + CLOSE(i)] / N

The smoothing factor is 1/N. So if you run a 20 SMMA, each new close only nudges the line a bit, while the prior value carries most of the weight.

SMMA Calculation Steps (Manual Method)

1. Pull N closing prices.

2. Add them up for the initial window.

3. Divide by N to get the first SMMA value.

4. After that, take the previous SMMA and multiply it by (N-1).

5. Add the current close, then divide by N to get the new SMMA.

If you want worked examples across different markets, this detailed SMMA calculation guide breaks it down cleanly.

SMMA Calculation Example

SMMA vs SMA and EMA: What Changes in Practice?

The real difference is how the line “remembers” price. SMA forgets anything outside the window, so it can jump when old data drops off. SMMA never fully drops old data, so it stays smooth.

Also worth knowing: an SMMA with period N is equivalent to an EMA with period (2N-1). In practice, that means a 20 SMMA behaves a lot like a 39 EMA in terms of smoothness.

Common settings like 14, 20, 26, 50, and 52 are popular because they’re responsive enough to follow trend, but they don’t react to every random wick. Smaller N speeds it up (more signals, more noise). Larger N slows it down (fewer signals, cleaner bias).

How Do You Know If SMMA Is Improving Your Results Over Time?

SMMA can help you stay aligned with trend and avoid noise, but the real question is whether it improves your execution in the markets you trade. The simplest way to validate that is to review trades taken with and without the SMMA filter: track entry type (pullback vs crossover), timeframe, market regime (trend vs range), and whether exits were managed using the line as dynamic support/resistance. Over a meaningful sample, those notes make it easier to spot where SMMA reduces whipsaws, where lag costs early entries, and which settings actually fit your volatility and stop placement.

To keep that process consistent, using a trade journal with performance tracking and analytics helps you connect indicator rules to outcomes—PnL, win rate, average R, and drawdown—rather than relying on memory. A structured dashboard such as Rizetrade trading journal analytics for tracking SMMA-based performance metrics can support that kind of review by organizing setups, tagging conditions, and comparing results across periods and instruments.