search for: archm

...sk-premium. I've implemented it like this: #specification of the model spec = ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1,1), submodel = NULL, external.regressors = NULL, variance.targeting = FALSE), mean.model = list( armaOrder = c(0,0), include.mean = TRUE, archm = TRUE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "jsu", start.pars = list(), fixed.pars = list()) #fit the model to historical closing price (prices) fit = ugarchfit(data = prices, spec = spec) #save coefficients of the fitted model...

My code: spec<-ugarchspec(variance.model = list(model = "sGARCH", garchOrder = c(1, 1), submodel = "Null", external.regressors = NULL, variance.targeting = FALSE), mean.model = list(armaOrder=c(0,0),include.mean =FALSE, archm = FALSE, archpow = 1, arfima = FALSE, external.regressors = NULL, archex = FALSE), distribution.model = "norm", start.pars = list(), fixed.pars = list()) ugarchfit(spec, X2, out.sample = 0, solver = "solnp", solver.control = list(trace = TRUE, tol=1e-4, delta=1e-8), fit.contr...