Smoothed Moving Average (2024)

FAQs

How to read smoothed moving average? ›

Interpretation of Smoothed Moving Average

SMA values above the current price indicate resistance levels, while values below the current price indicate support levels. Traders can identify trends by observing the direction of the moving average.

Calculate the Smoothed Moving Average: Starting from the second period onwards, you apply the smoothing factor to the current closing price and the previous SMA. The formula is: SMA = (Closing Price * Smoothing Factor) + (Previous SMA * (1 - Smoothing Factor))

Economists use a simple smoothing technique called “moving average” to help determine the underlying trend in housing permits and other volatile data. A moving average smoothes a series by consolidating the monthly data points into longer units of time—namely an average of several months' data.

A 9 or 10-day moving average period is the best-moving average for intraday trading. However, 21-day EMA can be also used for day trading but you have to apply another technical indicator in combination with moving averages crossover to know the trend reversal.

Recall that, as a general guideline, when the price is above a moving average, the trend is considered up. So when the price drops below the moving average, it signals a potential reversal based on that MA. A 20-day moving average will provide many more reversal signals than a 100-day moving average.

The Smoothed Moving Average (SMMA) indicator is an Exponential Moving Average (EMA) smoothed with a longer time period. SMMA takes more data points for calculation and provides more accurate results than Simple Moving Average (SMA) plotting the line with fewer fluctuations.

It's important for traders to remember that the Smoothed Moving Average is a function of weight in connection with price, or length of the average. Additionally, the Smoothed Moving Average uses a longer period in order to determine the average and assigns weight to price data while the average is calculated.

Moving averages are intended to remove the noise created by short-lived news and market sentiment. Common periods used are 100 days, 200 days, and 500 days for long-term investors, and five days, 10 days, 20 days, and 50 days for short-term trades.

Right settings for SMMA

It is up to each trader to work and find the periods that work well for them. Nonetheless, the most popular periods by short-term day traders are 14 and 28. For long-term traders, the most popular ones are the 50, 100, and 200-day moving averages.

How Does the 5-8-13 EMA Crossover Work? The crossover detects momentum shifts, which can hint at significant price moves in the near term. When the 5-EMA crosses above the 8 and 13 EMAs, it suggests a rising bullish momentum. When the opposite happens, it indicates bearish momentum.

Is EMA or SMA better for scalping? ›

The Exponential Moving Averages, or EMA, isn't just another average. It's a beacon for scalpers, shining light on recent price action trend. Unlike the Simple Moving Averages (SMA), which treats all price data equally, the EMA indicator places a higher emphasis on recent prices.

But everything else being equal, an EMA will track price more closely than an SMA. Because of this, the EMA is typically considered more appropriate in short-term trading. The same characteristics that make the EMA better suited for short-term trading limit its effectiveness when it comes to the long term.

The average is called "moving" because it is plotted on the chart bar by bar, forming a line that moves along the chart as the average value changes. SMAs are often used to determine trend direction. If the SMA is moving up, the trend is up. If the SMA is moving down, the trend is down.

The primary difference between an EMA and an SMA is the sensitivity each one shows to changes in the data used in its calculation. The exponential moving average gives a higher weighting to recent prices, while the simple moving average assigns an equal weighting to all values.

The SMA calculates the average price of an asset over a certain period, usually using closing prices. Then, it smooths out the data by giving more importance to recent prices. This smoothening process helps remove short-term price fluctuations and focuses on the overall trend of the asset.