[0.93, 0.9, 0.2]) print g11res llf = loglike_GARCH11(g11res, errgjr4 - errgjr4.mean()) print llf[0] if 'rpyfit' in examples: from rpy import r r.library('fGarch') f = r.formula('~garch(1, 1)') fit = r.garchFit(f, data=errgjr4 - errgjr4.mean(), include_mean=False) if 'rpysim' in examples: from rpy import r f = r.formula('~garch(1, 1)') #fit = r.garchFit(f, data = errgjr4) x = r.garchSim(n=500) print 'R acf', tsa.acf(np.power(x, 2))[:15] arma3 = Arma(np.power(x, 2)) arma3res = arma3.fit(start_params=[-0.2, 0.1, 0.5], maxiter=5000) print arma3res.params arma3b = Arma(np.power(x, 2)) arma3bres = arma3b.fit(start_params=[-0.2, 0.1, 0.5], maxiter=5000, method='bfgs') print arma3bres.params xr = r.garchSim(n=100) x = np.asarray(xr) ggmod = Garch(x - x.mean()) ggmod.nar = 1
print('ggres0.params', ggres0.params) ggmod0 = Garch0(errgjr4-errgjr4.mean())#hgjr4[:nobs])#-hgjr4.mean()) #errgjr4) ggmod0.nar = 1 ggmod.nma = 1 start_params = np.array([-0.6, 0.2, 0.1]) ggmod0._start_params = start_params #np.array([-0.6, 0.1, 0.2, 0.0]) ggres0 = ggmod0.fit(start_params=start_params, method='bfgs', maxiter=2000) print('ggres0.params', ggres0.params) if 'rpy' in examples: from rpy import r f = r.formula('~garch(1, 1)') #fit = r.garchFit(f, data = errgjr4) x = r.garchSim( n = 500) print('R acf', tsa.acf(np.power(x,2))[:15]) arma3 = Arma(np.power(x,2)) arma3res = arma3.fit(start_params=[-0.2,0.1,0.5],maxiter=5000) print(arma3res.params) arma3b = Arma(np.power(x,2)) arma3bres = arma3b.fit(start_params=[-0.2,0.1,0.5],maxiter=5000, method='bfgs') print(arma3bres.params) llf = loglike_GARCH11([0.93, 0.9, 0.2], errgjr4) print(llf[0]) erro,ho, etaxo = generate_gjrgarch(20, ar, ma, mu=0.04, scale=0.01, varinnovation = np.ones(20))
g11res = optimize.fmin(lambda params: -loglike_GARCH11(params, errgjr4-errgjr4.mean())[0], [0.93, 0.9, 0.2]) print g11res llf = loglike_GARCH11(g11res, errgjr4-errgjr4.mean()) print llf[0] if 'rpyfit' in examples: from rpy import r r.library('fGarch') f = r.formula('~garch(1, 1)') fit = r.garchFit(f, data = errgjr4-errgjr4.mean(), include_mean=False) if 'rpysim' in examples: from rpy import r f = r.formula('~garch(1, 1)') #fit = r.garchFit(f, data = errgjr4) x = r.garchSim( n = 500) print 'R acf', tsa.acf(np.power(x,2))[:15] arma3 = Arma(np.power(x,2)) arma3res = arma3.fit(start_params=[-0.2,0.1,0.5],maxiter=5000) print arma3res.params arma3b = Arma(np.power(x,2)) arma3bres = arma3b.fit(start_params=[-0.2,0.1,0.5],maxiter=5000, method='bfgs') print arma3bres.params xr = r.garchSim( n = 100) x = np.asarray(xr) ggmod = Garch(x-x.mean()) ggmod.nar = 1 ggmod.nma = 1 ggmod._start_params = np.array([-0.6, 0.1, 0.2, 0.0])