Hi all,
there is one issue I can?t go one myself. I try to fit a nig-distribution in
a rolling window method to a time-series with the fantastic rugarch package.
I use the option 'calculate.VaR' for several other distributions and it
works fine, but if I switch to the nig-distribution, I recieve the following
warning:
In ans[i] = mu[i] + sigma[i] * .qsnigC(p, rho = skew[i], ... :number of
items to replace is not a multiple of replacement length
I tried to turn off the option and calculate the quantile on my own. I think
there is an misstake with the number of the parameters, but what can I
change to get over?
For code, see below
Best regards
library(quantmod)
library(rugarch)
library(PerformanceAnalytics)
bi <- getSymbols('^GDAXI', from = "2004-01-01", to = "2015-08-01")
bi <- Ad(get(bi[1]))
bi_tlr <- Return.calculate(bi, method = "log")
bi_tlr <- na.omit(bi_tlr)
ctrl = list(rho = 1, delta = 1e-11, outer.iter = 1000, tol = 1e-12)
cl = makePSOCKcluster(10)
T = nrow(bi_tlr)
t_bt <- nrow(as.xts(bi_tlr)["2006-01-01/2015-08-01"])
t_est <- T - t_bt
spec_nig = ugarchspec(variance.model = list(model = "sGARCH", garchOrder =
c(1,1)),
mean.model = list(armaOrder = c(0,0), include.mean = FALSE),
distribution.model = "nig")
bi.backtest.nig = ugarchroll(spec_nig, data = bi_tlr, n.ahead = 1,
forecast.length = 10, refit.every = 1, refit.window = "moving", solver =
"hybrid", fit.control = list(), solver.control = ctrl, calculate.VaR = TRUE,
VaR.alpha = c(0.01,0.05), cluster = cl,keep.coef = TRUE)
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VaR calculation warning with rugarch
3 messages · Mingersming, Alexios Ghalanos
You can ignore the warning. You can calculate the values yourself and
check that the results are the same:
df = as.data.frame(bi.backtest.nig)
q = quantile(bi.backtest.nig,0.01)
q10 =
qdist("nig",0.01,mu=0,sigma=df[10,"Sigma"],skew=df[10,"Skew"],shape=df[10,"Shape"])
as.numeric(q[10])==q10
> TRUE
q5 =
qdist("nig",0.01,mu=0,sigma=df[5,"Sigma"],skew=df[5,"Skew"],shape=df[5,"Shape"])
as.numeric(q[5])==q5
> TRUE
The warning will be fixed in the development version (...soon).
Alexios
On 16/08/2015 17:55, Mingersming wrote:
Hi all,
there is one issue I can?t go one myself. I try to fit a nig-distribution in
a rolling window method to a time-series with the fantastic rugarch package.
I use the option 'calculate.VaR' for several other distributions and it
works fine, but if I switch to the nig-distribution, I recieve the following
warning:
In ans[i] = mu[i] + sigma[i] * .qsnigC(p, rho = skew[i], ... :number of
items to replace is not a multiple of replacement length
I tried to turn off the option and calculate the quantile on my own. I think
there is an misstake with the number of the parameters, but what can I
change to get over?
For code, see below
Best regards
library(quantmod)
library(rugarch)
library(PerformanceAnalytics)
bi <- getSymbols('^GDAXI', from = "2004-01-01", to = "2015-08-01")
bi <- Ad(get(bi[1]))
bi_tlr <- Return.calculate(bi, method = "log")
bi_tlr <- na.omit(bi_tlr)
ctrl = list(rho = 1, delta = 1e-11, outer.iter = 1000, tol = 1e-12)
cl = makePSOCKcluster(10)
T = nrow(bi_tlr)
t_bt <- nrow(as.xts(bi_tlr)["2006-01-01/2015-08-01"])
t_est <- T - t_bt
spec_nig = ugarchspec(variance.model = list(model = "sGARCH", garchOrder =
c(1,1)),
mean.model = list(armaOrder = c(0,0), include.mean = FALSE),
distribution.model = "nig")
bi.backtest.nig = ugarchroll(spec_nig, data = bi_tlr, n.ahead = 1,
forecast.length = 10, refit.every = 1, refit.window = "moving", solver =
"hybrid", fit.control = list(), solver.control = ctrl, calculate.VaR = TRUE,
VaR.alpha = c(0.01,0.05), cluster = cl,keep.coef = TRUE)
--
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1 day later
Okay, I thought there was a generally mistake by myself. Because I saw the same warnings with my quantil approach. But now it?s clear, after I saw the same warnings with your code. I was confused about the running time compared to the "easier" distributions, and thought the calculation was stucked. I saw the CPU-usage running down after a few minutes. So, i suggested the tasks run into a overflow or something like that. For my clarity: the solver extract firstly the model parameters (with 100 percent CPU-usage) and calculate afterwards the quantile? After some benchmarking I think the "nig" model takes 9x of the time it does take to fit the "norm" model. Thank you, for your quick response! Best Re -- View this message in context: http://r.789695.n4.nabble.com/VaR-calculation-warning-with-rugarch-tp4711164p4711204.html Sent from the Rmetrics mailing list archive at Nabble.com.