小编Wig*_*ums的帖子

我正在尝试，类似于 R 的 ugarch

# standard GARCH model with optional ARMA part
        spec <- ugarchspec(variance.model = list(model = "sGARCH",    garchOrder = c(r,s)),
                           mean.model     = list(armaOrder = c(p,q)), distribution.model = dist[1])

ugarchfit(spec, data = x[,i], solver = "hybrid", fit.control = list(scale = 1),
                             numderiv.control = list(hess.eps = 1e-2))

使用 ARCH 库将联合 ARIMA(p,0,q)-GARCH(r,s) 拟合到几个时间序列。基于几种测试方法，我想找出 p,q,r,s 的最佳拟合参数。
基于 ARCH 文档均值模型可以选择No Mean、Constant Mean、Autoregressions和Heterogeneous Autoregressions。

arch.arch_model(y, x=None, mean='Constant', lags=0, vol='Garch', p=1, o=0, q=1, power=2.0, dist='Normal', hold_back=None)[source]

如何在 …