# Why Is the Triple Exponential Moving Average (TEMA) Important for Traders and Analysts?

The triple exponential moving average (TEMA) is important for traders and analysts because it is useful as a trend indicator in otherwise choppy markets. It reduces the effects of relatively large price fluctuations and helps to filter out volatility.

### Key Takeaways

• The triple exponential moving average (TEMA) is a modified moving average designed to smooth large price fluctuations.
• This makes it easier to identify trends without the lag associated with traditional moving averages.
• It does this by taking multiple exponential moving averages (EMA) of the original EMA and subtracting out some of the lag.

## Functions of the Triple Exponential Moving Average

The triple exponential moving average is a modified moving average that was created in the mid-1990s by Patrick Mulloy. This average was developed to avoid the inevitable issue of lag that traders encounter when using oscillators or exponential moving averages (EMAs). Using multiple moving averages of price smooths out short-term fluctuations. What makes the TEMA so effective is that it uses successive EMAs of EMAs, and the formula includes an adjustment for lagging.

The TEMA serves as a trend indicator. It is not as successfully employed in a ranging market. The TEMA is most easily used for trading purposes with trends sustained over long periods of time. With longer trends, analysts can more easily filter out and disregard periods of volatility. Using the TEMA with a variety of other oscillators or technical indicators can help traders and analysts to interpret sharp price fluctuations and evaluate volatility. Some analysts recommend a combination of the moving average convergence divergence (MACD) and the TEMA for evaluating market trends.

## Calculating the Triple Exponential Moving Average

To calculate the TEMA, once an analyst has chosen a time period, he calculates the initial EMA. Then, a second EMA, the double exponential moving average (DEMA), is calculated from the initial EMA. The final step in calculating the TEMA is to take a third EMA from the DEMA.

TEMA =(3∗EMA1)−(3∗EMA2 )+EMA3

​where:

• EMA1 ​= Exponential Moving Average (EMA)
• EMA2 =EMA of EMA1
• EMA3 ​= EMA ofEMA2
1. ​Choose a lookback period. This is how many periods will be factored into the first EMA. With a fewer number of periods, like 10, the EMA will track price closely and highlight short-term trends. With a larger lookback period, like 100, the EMA will not track price as closely and will highlight the longer-term trend.
2. Calculate the EMA for the lookback period. This is EMA1.
3. Calculate the EMA of EMA1, using the same lookback period. For example, if using 15 periods for EMA1, use 15 in this step as well. This is EMA2.
4. Calculate the EMA of EMA2, using the same lookback period as before.
5. Plug EMA1, EMA2, and EMA3 into the TEMA formula to calculate the triple exponential moving average.

## Why Is TEMA Important for Trading?

The TEMA reacts to price changes quicker than a traditional MA or EMA will. This is because some of the lag has been taken out in the calculation. A TEMA can be used in the same ways as other types of moving averages.

Mainly, the direction TEMA is angled indicates the short-term (averaged) price direction. When the line is sloping up, that means the price is moving up. When it is angled down, the price is moving down. There is still a small amount of lag in the indicator, so when price changes quickly the indicator may not change its angle immediately. Also, the larger the lookback period, the slower the TEMA will be in changing its angle when price changes direction.

The TEMA may also provide indications of support or resistance for the price. For example, when the price is rising overall, on pullbacks it may drop to the TEMA, and then the price may appear to bounce off of it and keep rising. This movement is reliant upon the proper look back period for the asset. If using the TEMA for this purpose, it should have already provided support and resistance in the past. If the indicator didn't provide support or resistance in the past, it probably won't in the future.

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Article Sources
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1. Mulloy, Patrick. "Smoothing Data With Faster Moving Averages." Stocks & Commodities Magazine, volume 12, no1, 1994, pp. 11-19.

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