fMultivar (version 251.70)

RollingAnalysis: Rolling Analysis

Description

A collection and description of functions to perform a rolling analysis. A rolling analysis is often required in building trading models. The functions are: ll{ rollFun Rolling or moving sample statistics, rollMin Rolling or moving sample minimum, rollMax Rolling or moving sample maximum, rollMean Rolling or moving sample mean, rollVar Rolling or moving sample variance. }

Usage

rollFun(x, n, trim = TRUE, na.rm = FALSE, FUN, ...)
rollMin(x, n = 9, trim = TRUE, na.rm = FALSE) 
rollMax(x, n = 9, trim = TRUE, na.rm = FALSE)
rollMean(x, n = 9, trim = TRUE, na.rm = FALSE)
rollVar(x, n = 9, trim = TRUE, unbiased = TRUE, na.rm = FALSE)

Arguments

FUN

the rolling function, arguments to this function can be passed through the ... argument.

n

an integer specifying the number of periods or terms to use in each rolling/moving sample.

na.rm

a logical flag: if TRUE, missing values in x will be removed before computation. The default is FALSE.

trim

a logical flag: if TRUE, the first n-1 missing values in the returned object will be removed; if FALSE, they will be saved in the returned object. The default is TRUE.

unbiased

a logical flag. If TRUE, the unbiased sample variance will be returned. The default is TRUE.

x

an univariate timeSeries object or a numeric vector.

...

additional arguments to be passed.

Value

• The functions return a timeSeries object or a numeric vector, depending on the argument x. rollMax returns the rolling sample maximum, rollMin returns the rolling sample minimum, rollMean returns the rolling sample mean, and rollVar returns the biased/unbiased rolling sample variance. Note, that the function rollFun always returns a numeric vector, independent of the argument x. If you like to operate for x with rectangular objects, you have to call the functions columnwise within a loop.

See Also

var.

Examples

## Rolling Analysis:
   x = (1:10)^2
   x
   trim =  c(TRUE, TRUE, FALSE, FALSE)
   na.rm = c(TRUE, FALSE, TRUE, FALSE)
   for (i in 1:4) 
     print(rollMin(x, 5, trim[i], na.rm[i]))
   for (i in 1:4) 
     print(rollMax(x, 5, trim[i], na.rm[i]))
   for (i in 1:4) 
     print(rollVar(x, 5, trim[i], unbiased = TRUE, na.rm[i]))
   for (i in 1:4) 
     print(rollVar(x, 5, trim[i], unbiased = FALSE, na.rm[i]))