Input Information
Name | Expression | Default | Description |

Market Synopsis
Table of Content:
- Introduction
- What is SMMA?
- How does SMMA work?
- Custom Moving Average
- Advantages of SMMA
- Disadvantages of SMMA
Introduction:
In technical analysis, moving averages are commonly used for smoothing out price data to identify trends and potential buy/sell signals. One such moving average is the Smoothed Moving Average (SMMA).
What is SMMA?
SMMA is a type of moving average that places more weight on recent data points than on older data points. This is done by applying a smoothing factor to the data. The formula for SMMA involves taking the sum of the previous n periods’ closing prices and multiplying it by a weighting factor. The result is then divided by the sum of the weighting factor.
How does SMMA work?
The SMMA is calculated as follows:
- Calculate the sum of the previous n periods’ closing prices
- Multiply this sum with a weighting factor (usually between 1 and 10)
- Divide the result by the sum of the weighting factor
- This gives you the SMMA value for that period
As new data points are added, the SMMA is recalculated, giving more weight to the most recent data points and less weight to older data points.
Custom Moving Average:
SMMA is a type of custom moving average because the calculation formula can be adjusted to suit a trader’s needs. For example, a trader might decide to use a larger weighting factor to give even more importance to recent price data.
Advantages of SMMA:
- SMMA is useful for identifying trends in price data
- The smoothing factor reduces the impact of sudden spikes or drops in price, making it easier to identify the underlying trend
- The weighting factor can be adjusted to suit a trader’s needs
- SMMA is easy to calculate and interpret
Disadvantages of SMMA:
- SMMA can be slow to react to sudden changes in price, which may result in missed trading opportunities
- Traders need to adjust the weighting factor and period length depending on market conditions, which may require constant monitoring and adjustment
- SMMA is not suitable for all types of markets, such as highly volatile markets
Smoothed Moving Average (SMMA)
The Smoothed Moving Average (SMMA) is a technical analysis indicator used to analyze price trends. It is a type of moving average that places greater emphasis on more recent data in the calculation of the average.
Custom Moving Average
A Custom Moving Average is a type of moving average that allows traders to adjust or customize the weighting given to each data point in the average calculation. This can help to reduce lag and provide more accurate signals.
SMMA vs Simple Moving Average (SMA)
The SMMA places more weight on recent data points, while the SMA gives equal weight to all data points. This means that the SMMA is more responsive to changes in price trends, but can potentially generate more false signals.
How to Calculate SMMA
To calculate the SMMA, you first need to choose a period (e.g. 20 days). Then, you take the sum of the closing prices for the chosen number of periods and divide by the chosen period to get the simple moving average (SMA).
Next, you calculate the smoothing factor by dividing the chosen period by 2 and adding 1 (e.g. for a 20-day period, the smoothing factor would be 11).
Finally, you apply the smoothing factor to the SMA using the following formula:
SMMA = (Previous SMMA x (Smoothing Factor – 1) + Closing Price) / Smoothing Factor
Benefits and Drawbacks of SMMA
- Benefits:
- More responsive to changes in price trends
- Can help to reduce lag
- Provides a smoother curve than other moving averages
- Drawbacks:
- Potentially generates more false signals
- Requires more complicated calculations
- May not work well in volatile markets
Plot Information
Number | Name | Default Color | Description |
Remarks
Indicators
- Accumulation Swing Index ASI
- Accumulation/Distribution AD
- Adaptive moving average
- Alligator (Gator_2)
- Alligator (Gator)
- Aroon Down Indicator
- Aroon Oscillator
- Aroon Up Indicator
- Average Directional Movement Index ADX
- Average True Range- ATR
- Awesome Oscillator
- Bears Power
- Bollinger Bands-BB
- Bubi Candles
- Bulls Power
- BW-ZoneTrade-BWZT
- Chaikin Oscillator
- Chaikin Volatility-CHV
- ColorBars
- ColorLine
- Commodities Channel Index- CCI
- Crossover of Moving Averages
- Demarker Indicator
- Detrended Price Oscillator-DPO
- Directional Indicators-DI
- Directional Movement Index-DMI
- Disparity Index
- Double exponential moving average
- Double Exponential Moving Average DEMA
- Dynamic Support and Resistance
- Envelopes
- Exponential Moving Average-EMA
- Force Index
- Fractal Adaptive Moving Average-FrAMA
- Fractals
- Heikin Ashi
- Ichimoku Kinko Hyo (ichimoku)
- Keltner channel
- Market Facilitation Index
- Mass Index indicator (MI)
- McClellan Oscillator
- Momentum
- Money Flow Index MFI
- Moving Average
- Moving Average Convergence/ Divergence MACD MAC D
- Moving Average MV
- Moving Average of Oscillator
- On Balance Volume OBV
- Oscillator of a Moving Average OsMA ( MACD Histogram)
- Parabolic
- Parabolic SAR
- Price and Volume Trend (VPT) Indicator
- Price Channel Indicator
- Range Indicator
- Rate of Change ROC
- Relative Strength Index RSI
- Relative Vigor Index RVI
- Simple Moving Average SMA
- Smoothed Moving Average SMMA Custom Moving Average
- Standard Deviation (StdDev)
- Stochastic Oscillator
- The triple exponential average TRIX indicator
- Triple Exponential Average
- Triple Exponential Moving Average TEMA
- Triple Moving Average Crossover
- True Strength Index TSI
- Ultimate Oscillator
- Variable index Dynamic Average (VIDYA)
- Volume Rate of Change VROC
- Weighted Moving Average WMA
- Williams’ Percent Range-Williams %R Larry Williams Percentage Range (WPR)
Fundamental Summary
- Coming soon!!