Library: | times |
See also: | lo kpss rvlm robwhittle roblm gph pgram |
Quantlet: | lobrob | |
Description: | Semiparametric test for I(0) of a time series against fractional alternatives, i.e., long-memory and antipersistence. The test is semiparametric in the sense that it does not depend on a specific parametric form of the spectrum in the neighborhood of the zero frequency. The first argument of the function is the series. The second optional argument is the vector of bandwidth, i.e., the parameter specifying the number of harmonic frequencies around zero to be considered. By default, the quantlet uses the automatic bandwidth given in Lobato and Robinson. If the user provides his own vector of bandwidths, then the function returns the value of the test for each component of the bandwidth vector. If the value of the test is in the lower tail of the standard normal distribution, the null hypothesis of I(0) is rejected against the alternative that the series displays long-memory. If the value of the test is in the upper tail of the standard normal distribution, the null hypothesis I(0) is rejected against the alternative that the series is antipersistent. |
Usage: | T = lobrob(y{,bdvec}) | |
Input: | ||
y | vector | |
bdvec | vector | |
Output: | ||
T | vector |
;Test for long-memory in the volatility. As there is no optional ;argument, the automatic bandwidth is used library("times") x = read("dmus58.dat") x=x[1:1000] y = abs(tdiff(x)) T = lobrob(y) T
; As T is negative, and in the lower tail of the standard normal ; distribution, there is evidence of long-memory in the volatility ; The automatic bandwidth is equal to 301 Contents of T [1,] Bandwidth Statistic [2,] _____________________ [3,] [4,] 301 -3.8377
;The same as above, except that a 3-dimensional vector m of ;bandwidth is provided as optional second argument. library("times") x = read("dmus58.dat") x=x[1:1000] y = abs(tdiff(x)) m = #(150,200,250) T = lobrob(y,m) T
; T is negative, thus we also conclude that there is evidence for ; long-memory in the volatility for m = 150, 200, 250 Contents of T [1,] Bandwidth Statistic [2,] _____________________ [3,] [4,] 150 -2.7637 [5,] 200 -3.4422 [6,] 250 -3.2086