Hello, I'm Gregory!

import numpy as np import pandas as pd from scipy.optimize import minimize import matplotlib.pyplot as plt def nelson_siegel_svensson(maturity, beta0, beta1, beta2, beta3, tau1, tau2): """ Nelson-Siegel-Svensson yield curve model """ term1 = beta1 * ((1 - np.exp(-maturity/tau1)) / (maturity/tau1)) term2 = beta2 * (((1 - np.exp(-maturity/tau1)) / (maturity/tau1)) - np.exp(-maturity/tau1)) term3 = beta3 * (((1 - np.exp(-maturity/tau2)) / (maturity/tau2)) - np.exp(-maturity/tau2)) return beta0 + term1 + term2 + term3 # Optimize parameters for yield curve fitting def optimize_nss_parameters(market_yields, maturities): result = minimize(objective_function, initial_params, args=(market_yields, maturities), method='L-BFGS-B') return result.x