trdes: Exponentially Smoothed Trend

In FRAPO: Financial Risk Modelling and Portfolio Optimisation with R

Description

Calculation of the exponentially smoothed trend as a technical trading indicator.

Usage

trdes(y, lambda, init = NULL)

Arguments

y	Objects of classes: numeric, matrix, data.frame, ts, mts, and timeSeries are supported.
lambda	Numeric, the smoothing parameter for λ in the equation below. The value for the parameter must be in the interval 0 < λ < 1.
init	The initial value in the recursive calculation of the filter. Specifies the initial values of the time series just prior to the start value, in reverse time order. The default, i.e. NULL, is a set of zeros.

Details

The exponetially smoothed trend is calculated according to the formula:

z_t = λ y_t + (1 - λ) * z_{t-1}

Value

An object of the same class as y, containing the computed exponetially smoothed values.

Methods

y = "data.frame"

The calculation is applied per column of the data.frame and only if all columns are numeric.

y = "matrix"

The calculation is applied per column of the matrix.

y = "mts"

The calculation is applied per column of the mts object. The attributes are preserved and an object of the same class is returned.

y = "numeric"

Calculation of the es trend.

y = "timeSeries"

The calculation is applied per column of the timeSeries object and an object of the same class is returned.

y = "ts"

Calculation of the es trend. The attributes are preserved and an object of the same class is returned.

y = "xts"

Calculation of the es trend. The attributes are preserved and an object of the same class is returned.

y = "zoo"

Calculation of the es trend. The attributes are preserved and an object of the same class is returned.

Author(s)

Bernhard Pfaff

See Also

filter, trdbilson, trdbinary, trdhp, trdsma, trdwma, capser

Examples

data(StockIndex)
y <- StockIndex[, "SP500"]
yret <- diff(log(y))
es <- trdes(yret, lambda = 0.95)
head(es)

FRAPO documentation built on May 2, 2019, 5:24 p.m.