smoothts (Financial Time Series Toolbox)

Smooth data

Syntax

output = smoothts(input)
output = smoothts(input, 'b', wsize)
output = smoothts(input, 'g', wsize, stdev)
output = smoothts(input, 'e', n)

Arguments

input

A financial time series object or a row-oriented matrix. In a row-oriented matrix each row represents an individual set of observations.

'b', 'g', or 'e'
Smoothing method (essentially the type of filter used). May be Exponential (e), Gaussian (g), or Box (b). Default = b.

wsize
Window size (scalar). Default = 5.

stdev
Scalar that represents the standard deviation of the Gaussian window. Default = 0.65.

n
For Exponential method, specifies window size or exponential factor, depending upon value.
n > 1 (window size) or period length
n < 1 and > 0 (exponential factor: alpha)
n = 1 (either window size or alpha)
If n is not supplied, the defaults are wsize = 5 and alpha = 0.3333.

`input`	A financial time series object or a row-oriented matrix. In a row-oriented matrix each row represents an individual set of observations.
`'b', 'g', or 'e'`	Smoothing method (essentially the type of filter used). May be Exponential (`e`)`,` Gaussian (`g`), or Box (`b`). Default = `b`.
`wsize`	Window size (scalar). Default = 5.
`stdev`	Scalar that represents the standard deviation of the Gaussian window. Default = 0.65.
`n`	For Exponential method, specifies window size or exponential factor, depending upon value. `n > 1` (window size) or period length `n < 1` and `> 0` (exponential factor: alpha) `n = 1` (either window size or alpha) If `n` is not supplied, the defaults are `wsize = 5` and `alpha = 0.3333`.

Description

smoothts smooths the input data using the specified method.

output = smoothts(input) smooths the input data using the default Box method with window size, wsize, of 5.

output = smoothts(input, 'b', wsize) smooths the input data using the Box (simple, linear) method. wsize specifies the width of the box to be used.

output = smoothts(input, 'g', wsize, stdev) smooths the input data using the Gaussian window method.

output = smoothts(input, 'e', n) smooths the input data using the Exponential method. n can represent the window size (period length) or alpha. If n > 1, n represents the window size. If 0 < n < 1, n represents alpha, where

If input is a financial time series object, output is a financial time series object identical to input except for contents. If input is a row-oriented matrix, ouput is a row-oriented matrix of the same length.

See Also

tsmovavg

size sortfts