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| -rw-r--r-- | python/script_calibrate_tranches.py | 31 |
1 files changed, 31 insertions, 0 deletions
diff --git a/python/script_calibrate_tranches.py b/python/script_calibrate_tranches.py new file mode 100644 index 00000000..6368a74f --- /dev/null +++ b/python/script_calibrate_tranches.py @@ -0,0 +1,31 @@ +import numpy as np +from tranche_functions import GHquad, BClossdist + +n_int = 500 +n_credit = 100 +Z, w = GHquad(n_int) + +with open("recov.csv") as fh: + recov = np.array([float(e) for e in fh], dtype='double', order='F') + +with open("SurvProb.csv") as fh: + SurvProb = np.array([[float(e) for e in line.split(",")] for line in fh], dtype='double', order='F') + +defaultprob = 1 - SurvProb +p = defaultprob +rho = 0.45 * np.ones(n_credit) + +for l in range(150): + Rstoch = np.zeros((n_credit, n_int, SurvProb.shape[1])) + for t in range(SurvProb.shape[1]): + for i in range(n_credit): + Rstoch[i,:,t] = stochasticrecov(recov[i], 0, Z, w_mod, rho[i], defaultprob[i,t], p[i,t]) + L = np.zeros((n_int, Ngrid, SurvProb.shape[1])) + R = np.zeros((n_int, Ngrid, SurvProb.shape[1])) + for t in range(SurvProba.shape[1]): + S = 1 - Rstoch[:,:,t] + L[:,:,t] = lossdistZ(p[:,t], issuerweights, S, Ngrid, 0, rho, Z) + R[:,:,t] = lossdistZ(p[:,t], issuerweights, S, Ngrid, 0, rho, Z) + + for i in range(n_int): + result[:,i] = tranche.pvvec(Kmodified, L[i,,], R[i,,], cs) |