pymc.GARCH11#
- class pymc.GARCH11(*args, **kwargs)[source]#
GARCH(1,1) with Normal innovations. The model is specified by
\[y_t = \sigma_t * z_t\]\[\sigma_t^2 = \omega + \alpha_1 * y_{t-1}^2 + \beta_1 * \sigma_{t-1}^2\]with z_t iid and Normal with mean zero and unit standard deviation.
- Parameters
- omega: tensor
omega > 0, mean variance
- alpha_1: tensor
alpha_1 >= 0, autoregressive term coefficient
- beta_1: tensor
beta_1 >= 0, alpha_1 + beta_1 < 1, moving average term coefficient
- initial_vol: tensor
initial_vol >= 0, initial volatility, sigma_0
Methods
GARCH11.__init__
(omega, alpha_1, beta_1, ...)GARCH11.dist
(*args, **kwargs)Creates a tensor variable corresponding to the cls distribution.
GARCH11.logp
(x)Calculate log-probability of GARCH(1, 1) distribution at specified value.
Attributes
rv_class
rv_op