stochastics: Stochastic Oscillator / Stochastic Momentum Index

In TTR: Technical Trading Rules

Description

The stochastic oscillator is a momentum indicator that relates the location of each day's close relative to the high/low range over the past n periods. Developed by George C. Lane in the late 1950s. The SMI relates the close to the midpoint of the high/low range. Developed by William Blau in 1993.

Usage

  stoch(HLC, nFastK = 14, nFastD = 3, nSlowD = 3, maType,
    bounded = TRUE, smooth = 1, ...)

  SMI(HLC, n = 13, nFast = 2, nSlow = 25, nSig = 9, maType,
    bounded = TRUE, ...)

Arguments

HLC	Object that is coercible to xts or matrix and contains High-Low-Close prices. If only a univariate series is given, it will be used. See details.
n	Number of periods to use.
nFastK	Number of periods for fast %K (i.e. the number of past periods to use).
nFastD	Number of periods for fast %D (i.e. the number smoothing periods to apply to fast %K).
nSlowD	Number of periods for slow %D (i.e. the number smoothing periods to apply to fast %D).
smooth	Number of internal smoothing periods to be applied before calculating FastK. See Details.
nFast	Number of periods for initial smoothing.
nSlow	Number of periods for double smoothing.
nSig	Number of periods for signal line.
maType	Either: A function or a string naming the function to be called. A list with the first component like (1) above, and additional parameters specified as named components. See Examples.
bounded	Logical, should current period's values be used in the calculation?
...	Other arguments to be passed to the maType function in case (1) above.

Details

If a High-Low-Close series is provided, the indicator is calculated using the high/low values. If a vector is provided, the calculation only uses that series. This allows stochastics to be calculated for: (1) series that have no HLC definition (e.g. foreign exchange), and (2) stochastic indicators (e.g. stochastic RSI - see examples).

The smooth argument is the number of periods of internal smoothing to apply to the differences in the high-low-close range before calculating Fast K. Thanks to Stanley Neo for the suggestion.

Value

A object of the same class as HLC or a matrix (if try.xts fails) containing the columns:

fastK

Stochastic Fast %K

fastD

Stochastic Fast %D

slowD

Stochastic Slow %D

SMI

Stochastic Momentum Index

signal

Stochastic Momentum Index signal line

Note

The calculation for William's %R is similar to that of stochastics' fast %K.

The value for fast %K will be 0.5 whenever the highest high and lowest low are the same over the last n periods.

The stochastic oscillator and SMI calculate relative value of the close versus the high/low range and the midpoint of the high/low range, respectively.

The stochastic oscillator and the stochastic momentum index are interpreted similarly. Readings below 20 (above 80) are considered oversold (overbought). However, readings below 20 (above 80) are not necessarily bearish (bullish). Lane believed some of the best sell (buy) signals occurred when the oscillator moved from overbought (oversold) back below 80 (above 20).

For the stochastic oscillator, buy (sell) signals can also be given when %K crosses above (below) %D. Crossover signals are quite frequent however, which may result in whipsaws.

Author(s)

Joshua Ulrich

References

The following site(s) were used to code/document these indicators:
Stochastic Oscillator:
http://www.fmlabs.com/reference/StochasticOscillator.htm
http://www.equis.com/Customer/Resources/TAAZ?c=3&p=106
http://linnsoft.com/tour/techind/stoc.htm
http://stockcharts.com/education/IndicatorAnalysis/indic_stochasticOscillator.html

SMI:
http://www.fmlabs.com/reference/default.htm?url=SMI.htm

See Also

See EMA, SMA, etc. for moving average options; and note Warning section. See WPR to compare it's results to fast %K.

Examples

data(ttrc)
stochOSC <- stoch(ttrc[,c("High","Low","Close")])
stochWPR <- WPR(ttrc[,c("High","Low","Close")])

plot(tail(stochOSC[,"fastK"], 100), type="l",
    main="Fast %K and Williams %R", ylab="",
    ylim=range(cbind(stochOSC, stochWPR), na.rm=TRUE) )
lines(tail(stochWPR, 100), col="blue")
lines(tail(1-stochWPR, 100), col="red", lty="dashed")

stoch2MA <- stoch( ttrc[,c("High","Low","Close")],
    maType=list(list(SMA), list(EMA, wilder=TRUE), list(SMA)) )

SMI3MA <- SMI(ttrc[,c("High","Low","Close")],
    maType=list(list(SMA), list(EMA, wilder=TRUE), list(SMA)) )

stochRSI <- stoch( RSI(ttrc[,"Close"]) )

Example output

TTR documentation built on April 15, 2017, 8:31 a.m.