search for: garch_norm

...means no skewness (I can not find the paper defining the distribution). library(fSeries) curve(dsnorm(x, 0, 1, 1), -2, 2, add = F, col = 'red') #skew normal with skew 1 curve(dnorm(x, 0, 1), -2, 2, add = T, col = 'blue') #normal Then I try them as innovations, #normal innovation garch_norm <- garchFit(series = logr, include.mean = F) #skew normal innovation #this line do not include skew, so it got same result as normal garch_snorm <- garchFit(series = logr, cond.dist = 'dsnorm', include.mean = F, include.skew = F) #this line includes skew, but use default skew = 1,...

...m_fit <- snormFit(logr) curve(dsnorm(x, snorm_fit$est[1], snorm_fit$est[2], snorm_fit$est[3]), -.25, .15, add = TRUE, col=4) st_fit <- sstdFit(logr) curve(dsstd(x, st_fit$est[1], st_fit$est[2], st_fit$est[3], st_fit$est[4]), -.25, .15, add = TRUE, col=3) library(fSeries) #normal innovation garch_norm <- garchFit(series = logr, include.mean = F) #t inovation garch_t <- garchFit(series = logr, cond.dist = 'dstd', include.mean = F, include.shape = T) garch_t1 <- garchFit(series = logr, cond.dist = 'dstd', include.mean = F, shape = t_fit$est[3], include.shape = T) #skew n...