MovingAverages: Moving Averages

Description

Calculate various moving averages (MA) of a series.

Usage

SMA(x, n=10)
  EMA(x, n=10, wilder=FALSE, ratio=NULL)
  WMA(x, n=10, wts=1:n)
 DEMA(x, n=10)
EVWMA(price, volume, n=10)
ZLEMA(x, n=10, ratio=NULL)

Arguments

Vector to be averaged.

price

Vector of prices to be averaged.

volume

Volume series corresponding to price series, or a constant. See Notes.

Number of periods to average over.

wts

Vector of weights. Length of wts vector must equal the length of x, or n (the default).

wilder

logical; if TRUE, a Welles Wilder type EMA will be calculated; see notes.

ratio

A smoothing/decay ratio to use (overrides wilder in EMA)

Value

SMASimple moving average.
EMAExponential moving average.
WMAWeighted moving average.
DEMADouble-exponential moving average.
EVWMAElastic, volume-weighted moving average.
ZLEMAZero lag exponential moving average.

Warning

Some indicators (e.g. EMA, DEMA, EVWMA, etc.) are calculated using the indicators' own previous values, and are therefore unstable in the short-term. As the indicator receives more data, its output becomes more stable. See example below.

Details

SMA calculates the arithmetic mean of the series over the past n observations. EMA calculates an exponentially-weighted mean, giving more weight to recent observations. See Warning section below. WMA is similar to an EMA, but with linear weighting if the length of wts is equal to n. If the length of wts is equal to the length of x, the WMA will use the values of wts as weights. DEMA is calculated as: DEMA = 2 * EMA(x,n) - EMA(EMA(x,n),n). EVWMA uses volume to define the period of the MA. ZLEMA is similar to an EMA, as it gives more weight to recent observations, but attempts to remove lag by subtracting data prior to (n-1)/2 periods (default) to minimize the cumulative effect.

References

The following site(s) were used to code/document this indicator: http://www.fmlabs.com/reference/ExpMA.htm http://www.fmlabs.com/reference/WeightedMA.htm http://www.fmlabs.com/reference/DEMA.htm http://linnsoft.com/tour/techind/evwma.htm http://www.fmlabs.com/reference/ZeroLagExpMA.htm

Examples

Run this code

data(ttrc)
    ema.20 <-   EMA(ttrc[,"Close"], 20)
    sma.20 <-   SMA(ttrc[,"Close"], 20)
   dema.20 <-  DEMA(ttrc[,"Close"], 20)
  evwma.20 <- EVWMA(ttrc[,"Close"], 20)
  zlema.20 <- ZLEMA(ttrc[,"Close"], 20)

  ## Example of short-term instability of EMA
  ## (and other indicators mentioned above)
  x <- rnorm(100)
  tail( EMA(x[90:100],10), 1 )
  tail( EMA(x[70:100],10), 1 )
  tail( EMA(x[50:100],10), 1 )
  tail( EMA(x[30:100],10), 1 )
  tail( EMA(x[10:100],10), 1 )
  tail( EMA(x[ 1:100],10), 1 )

Run the code above in your browser using DataLab

Last chance! 50% off unlimited learning