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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.
Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned ...
The 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] The same article also introduced another EMA related indicator: Double exponential moving average (DEMA). [1] [2] [3]
An exponential moving average (EMA), also known as an exponentially weighted moving average (EWMA), [5] is a first-order infinite impulse response filter that applies weighting factors which decrease exponentially. The weighting for each older datum decreases exponentially, never reaching zero. This formulation is according to Hunter (1986). [6]
The MACD indicator thus depends on three time parameters, namely the time constants of the three EMAs. The notation "MACD(a,b,c)" usually denotes the indicator where the MACD series is the difference of EMAs with characteristic times a and b, and the average series is an EMA of the MACD series with characteristic time c. These parameters are ...
Moving average crossover of a 15-day exponential close-price MA (red) crossing over a 50-day exponential close-price MA (yellow) In the statistics of time series, and in particular the stock market technical analysis, a moving-average crossover occurs when, on plotting two moving averages each based on different degrees of smoothing, the traces of these moving averages cross.
[1] [2] [3] Using different time-steps or time-integrators in the context of a weak algorithm is rather straightforward, because the numerical solvers operate independently. However, this is not the case in a strong algorithm. In the past few years a number of research articles have addressed the development of strong multi-time-step algorithms.
The first frame of a longer multi-frame message packet, used when more than 6/7 bytes of data segmented must be communicated. The first frame contains the length of the full packet, along with the initial data. Consecutive frame (CF) 2: A frame containing subsequent data for a multi-frame packet Flow control frame (FC) 3