I would like to use my fitted heston model to generate paths to price an exotic type of option but I have a couple questions I can't seem to answer with the docs and examples. Why does the GaussianMultiPathGenerator or GaussianSobolMultiPathGenerator only take the process and not the model? the model contains the fitted parameters with the help of the volatility surfaces, but the process doesn't seem to contain a reference to those, how is it working? Should I fit the model, take the parameters and create a new process with the fitted parameters? dt = 1/252 # number of days from today to 31 march 2026 days = np.busday_count(pd.Timestamp.today().date(),pd.Timestamp('2026-03-31').date()) T = days*dt N_paths = 10000 N_steps = days busines_days = pd.bdate_range(start_date,periods=days) uniform_gen = ql.UniformRandomSequenceGenerator(int(2*N_steps),ql.UniformRandomGenerator()) gaussian_gen = ql.GaussianRandomSequenceGenerator(uniform_gen) times = list(ql.TimeGrid(T, int(N_steps))) multipath = ql.GaussianMultiPathGenerator(heston_process, times, gaussian_gen, False) Continue reading...
