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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]
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 simple moving average, or SMA, is one of the most common pieces of technical data that investors rely on. In the case of the 200-day SMA, it shows you the stock's average price over the past ...
Laplacian smoothing: algorithm to smooth a polygonal mesh. [4] [5] Local regression also known as "loess" or "lowess" a generalization of moving average and polynomial regression. fitting simple models to localized subsets of the data to build up a function that describes the deterministic part of the variation in the data, point by point
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.
Trix is calculated with a given N-day period as follows: Smooth prices (often closing prices) using an N-day exponential moving average (EMA). Smooth that series using another N-day EMA. Smooth a third time, using a further N-day EMA. Calculate the percentage difference between today's and yesterday's value in that final smoothed series.
The formula for a given N-Day period and for a given data series is: [2] [3] = = + (()) = (,) The idea is do a regular exponential moving average (EMA) calculation but on a de-lagged data instead of doing it on the regular data.
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