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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]
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. Data is de-lagged by removing the data from "lag" days ago thus removing (or attempting to) the cumulative effect of the moving average.
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 ...
Momentum is the change in an N-day simple moving average (SMA) between yesterday and today, with a scale factor N+1, i.e. + = This is the slope or steepness of the SMA line, like a derivative. This relationship is not much discussed generally, but it's of interest in understanding the signals from the indicator.
Average true range (ATR) is a technical analysis volatility indicator originally developed by J. Welles Wilder, Jr. for commodities. [1] [2] The indicator does not provide an indication of price trend, simply the degree of price volatility. [3]
Exponential Utility Function for different risk profiles. In economics and finance, exponential utility is a specific form of the utility function, used in some contexts because of its convenience when risk (sometimes referred to as uncertainty) is present, in which case expected utility is maximized. Formally, exponential utility is given by:
The Triple Exponential Moving Average (TEMA) is a technical indicator in technical analysis that 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 triple exponential smoothing which is not the case.