def generate_garch(nobs, ar, ma, mu=1.0, scale=0.1):
 eta = (scale * np.random.randn(nobs))
 h = signal.lfilter(ma, ar, (eta ** 2))
 err = (np.sqrt(h) * eta)
 return (err, h)

def generate_garch ( nobs , ar , ma , mu = 1.0 , scale = 0.1 ) : eta = ( scale * np . random . randn ( nobs ) ) h = signal . lfilter ( ma , ar , ( eta ** 2 ) ) err = ( np . sqrt ( h ) * eta ) return ( err , h )
simulate standard garch scale : float scale/standard deviation of innovation process in garch process .