The Double Exponential Moving Average (DEMA) indicator was introduced in January 1994 by Patrick G. Mulloy, in an article in the "Technical Analysis of Stocks & Commodities" magazine: "Smoothing Data with Faster Moving Averages"[1][2]

It attempts to remove the inherent lag associated with Moving Averages by placing more weight on recent values. The name suggests this is achieved by applying a double exponential smoothing which is not the case. The name double comes from the fact that the value of an EMA (Exponential Moving Average) is doubled. To keep it in line with the actual data and to remove the lag the value "EMA of EMA" is subtracted from the previously doubled ema.

The formula is:[3][4][5]

Because EMA(EMA) is used in the calculation, DEMA needs 2 × period - 1 samples to start producing values in contrast to the period samples needed by a regular EMA

The same article also introduced another EMA related indicator: Triple exponential moving average (TEMA)

As shown in the formula it reduces the weight on the recent values and by calculating ema of the ema we are trying to remove the weight on the long slower part of the average that has built up over time. It significantly helps make quicker decisions than the simple MA crossovers. Available on almost all the trading software now, it is much better than as it helps capture the trend earlier and make better decisions in the sense that helps one make better entry and exit points improving profitability.

References

edit
edit

📚 Artikel Terkait di Wikipedia

Triple exponential moving average

Triple Exponential Moving Average (TEMA) is a technical indicator in technical analysis that attempts to remove the inherent lag associated with moving averages

Zero lag exponential moving average

indicators which average a price over time. As is the case with the double exponential moving average (DEMA) and the triple exponential moving average (TEMA) this

Exponential smoothing

Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function

Autoregressive integrated moving average

autoregressive integrated moving average (ARIMA) and seasonal ARIMA (SARIMA) models are generalizations of the autoregressive moving average (ARMA) model to non-stationary

True strength index

again by a second moving average. The calculation for TSI uses exponential moving averages. The formula for the TSI is: T S I ( m , r , s ) = 100 E M A

Trix (technical analysis)

triple-smoothed exponential moving average. The name Trix is from "triple exponential." TRIX is a triple smoothed exponential moving average used in technical

Mass index

calculating its exponential moving average over a 9-day period and the exponential moving average of this average (a "double" average), and summing the

List of dynamical systems and differential equations topics

system analysis Takens' theorem Exponential dichotomy Liénard's theorem Krylov–Bogolyubov theorem Krylov-Bogoliubov averaging method Measure-preserving dynamical