Double Exponential Moving Average (DEMA)

The Double Exponential Moving Average (DEMA) offers traders a powerful way to spot market trends with greater precision than traditional indicators. This advanced tool combines two exponential moving averages to reduce lag time and capture price movements more effectively. While many traders rely on basic moving averages, DEMA’s unique calculation method helps cut through market noise and identify genuine trading opportunities. Understanding its core principles opens the door to more sophisticated trading strategies.

TLDR

• DEMA provides faster response to price changes than traditional moving averages, enabling traders to identify market trends more quickly.
• Combining DEMA with RSI and MACD creates a robust trading system that filters out market noise and reduces false signals.
• Multi-timeframe analysis using DEMA confirms trend strength and optimal entry points across different market conditions.
• Setting stop-loss levels below DEMA support points helps protect capital while maximizing potential returns in trading.
• DEMA’s unique calculation method, using double EMA smoothing, reduces lag time and improves signal accuracy for better trading decisions.

Why DEMA Was Invented

Patrick Mulloy invented the DEMA in  the 1990’s and wanted an indicator that could take out some of the lag associated with moving averages.  While 100% removal of lag is not possible with indicators derived from price, this reduction in lag produces an indicator that is more responsive to price changes.

This daily stock chart of Apple has the DEMA, the EMA, and a simple moving average overlayed.  All periods are set to 20.  It is clear that the DEMA stays extremely close to price which will have the indicator reacting quicker to changes in price than the other two.

The quicker reactions may suit the needs of short-term traders and swing traders as they look to be responsive to changes in the volatility and trend reversals in price.  Longer term investors may not be as concerned with getting shorter term changes in the market unless the longer term trend is affected.

How to Calculate the Double Exponential Moving Average (DEMA)

Mulloy explained in Technical Analysis of Stocks & Commodities magazine that he used the following for the formula:  DEMA = ( 2 * EMA(n)) – (EMA(n) of EMA(n) ).

N is the lookback period which can be any number you choose.

While it may look confusing, we simply:

+ Multiply a standard EMA by 2

+ Use another EMA with the same look back which acts as a smoothing EMA

+ Then multiply the EMA by 2 and subtract the smoothed EMA

Essentially, we are using the EMA of an EMA for the indicator plot that appears on your price chart.  While knowing what is behind the indicator is useful, your trading software will do the heavy lifting for you.

Trading With The DEMA – Complete HOW-TO

At it’s core, this is just another moving average and traders will use it much in the same way as any other one.

From trend direction and support and resistance to using moving average crossovers, there are a variety of ways to use them in your trading strategy.

One thing that is important is the lookback period.

Because of the lagging feature and how you plan on using the DEMA, some periods mingle with price making them not too helpful.

One feature of a moving average that is helpful is when the average “snakes” through the candlesticks.  This is often a sign of a choppy market and the formation of trading range.

If using the 9 period black line, the indicator stays inside of price for a majority of the time even when price is trending.  That takes away the choppy market indication and a trader would need to read price action for that market condition.  The 20 period green line and the red 50-day DEMA don’t engage with price as much.

The lower the lookback period, the more volatile the indicator will be.  A higher setting has less whipsaw and may be more useful.

Successful traders use several advanced strategies when incorporating DEMA into their trading systems.

One key approach involves multi timeframe analysis, where traders examine DEMA signals across different time frames to confirm trend strength and potential entry points. This helps filter out false signals and provides a more comprehensive market view.

Strategy optimization plays a role in maximizing DEMA’s effectiveness.

Traders adjust their lookback periods based on market conditions and combine DEMA with other technical indicators like RSI or MACD. This creates a strong trading system that can adapt to various market scenarios while maintaining reliable signal generation

Support and Resistance

This is where price will seemingly be bouncing off the moving averages.  I personally don’t follow that line of education and discard the notion that moving averages act as support and resistance.  There are many types of moving averages, from the Hull to the a simple average and it is naïve to think “institutions watch them” which is why they work.

When you find price reacting to an area around any moving average, look left and you will no doubt find some price structure that is holding price.

Trend Direction

With the less lag feature, using the double exponential moving average as a trend filter as you do other moving averages is viable. In this case, you would be alerted to a change in direction earlier than a standard moving average.

The key is what you determine to be a trend change:

+ Is it the slope of the moving average?

+ If price crosses the average, did the trend change direction?

+ Do you need price holding above or below the DEMA for a change in trend?

On this daily chart of Bitcoin using a 20 period DEMA, we have multiple trend changes using price trading above or below the average.

For this example, we look for price to break the average and then have some trading activity after the break.  We would ignore weak breaks and look for those that are done with some momentum. We can also look for lows above or highs below the average to signal a change as shown in the next example.

In the chart below, we have price breaking the DEMA and plotting two higher lows completely above the average or two lower highs below.

We would consider a break of the highest high or lowest low as confirmation of the trend change.

Traders would then use whatever trading strategy they use to find an entry point into the market for a trade.

Using Two DEMA Indicators

A very popular approach to trading is the crossover of two or more moving averages as part of a trading strategy. While trading the actual cross is not a suggested approach, we can use the indicators for a trend determination and an area of value for a pullback.

For a trend change, we would use the trend direction method we’ve already discussed.  We are able to add another layer of confirmation by requiring the 15 DEMA have crossed over or below the 50 DEMA.

Traders would look for a pullback into an area of value between the 15 and the 50.  Bear flags and bull flags, along with triangles, are my favorite patterns to look for on the charts.   Using the area of value ensures that price is showing a reaction against the main direction of price.  This avoids trading in a slow grinding market as we can see on the left of this chart.

Best Practices for DEMA Implementation

Successful DEMA implementation builds upon sound risk management principles with specific best practices that improve trading effectiveness. When setting DEMA parameters, traders should focus on timeframes that match their trading style while remaining mindful of market conditions. Clear DEMA signals emerge through careful observation and patience.

• Start with longer timeframe analysis to identify the primary trend before moving to shorter timeframes.
• Confirm DEMA signals with supporting indicators to reduce false entries.
• Practice proper position sizing and maintain stop-loss orders regardless of DEMA signal strength.

These practices help traders maintain consistency and discipline while using DEMA effectively in their trading strategy.

Your Questions Answered

How Does DEMA Perform Compared to Triple Exponential Moving Average (TEMA)?

DEMA advantages include faster response to price changes and less lag compared to TEMA, making it more suitable for short-term trading.

While TEMA provides smoother signals in trending markets, its main drawbacks are increased lag time and complexity in calculation.

DEMA strikes a better balance between smoothing and responsiveness, though both indicators can be useful depending on market conditions and trading timeframes.

Can DEMA Be Effectively Applied to Cryptocurrency Trading on Shorter Timeframes?

DEMA can be effectively used in cryptocurrency trading on shorter timeframes due to its quick responsiveness to price changes.

However, crypto volatility requires careful consideration when implementing DEMA-based strategies. Traders should use longer lookback periods during highly volatile periods to reduce false signals, while shorter periods work better in more stable conditions.

Combining DEMA with other technical indicators can help confirm trading signals.

What Programming Languages Are Best for Coding Custom DEMA Indicators?

Python is widely favored for DEMA coding due to its extensive libraries like Pandas and NumPy, making calculations straightforward.

R offers specialized packages for technical analysis, while C++ provides superior performance for high-frequency trading systems.

Java’s integration capabilities make it suitable for larger trading platforms.

Each language has its strengths, but Python remains the most accessible choice for beginners developing custom DEMA indicators.

Does DEMA Work Better With Specific Asset Classes Over Others?

DEMA performs particularly well with stocks and forex markets due to their predictable stock volatility patterns and established trading strategies.

However, its effectiveness varies across different market conditions rather than specific asset classes.

While DEMA can be applied to any tradable asset, it works best in markets with clear trending patterns and moderate volatility levels, regardless of the asset type.

How Do Seasonal Market Patterns Affect Dema’s Accuracy?

Seasonal trends can significantly impact DEMA’s performance, as market volatility often follows predictable annual patterns. During high-volatility seasonal periods, DEMA may generate more false signals, requiring traders to adjust their strategies.

Conversely, during stable seasonal phases, DEMA tends to provide more reliable signals. Understanding these seasonal market patterns helps traders optimize their DEMA settings and improve overall trading accuracy.

Conclusion

DEMA is a powerful tool for traders seeking to improve their market analysis and decision-making. By combining rapid responsiveness with reduced lag, it offers clear signals for entry and exit positions. When integrated with other technical indicators and proper risk management, DEMA provides a reliable framework for trading success. Its practical applications across various market conditions make it an essential component of any serious trader’s toolkit.