1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
|
import numpy as np
from tranche_functions import *
from yieldcurve import YC
import yaml
import datetime
import os
import pandas as pd
import pdb
n_int = 500
n_credit = 100
Z, w = GHquad(n_int)
with open("../R/index_definitions.yml") as fh:
indices = yaml.load(fh)
indices['hy21']['maturity'] = datetime.date(1970, 1, 1) + datetime.timedelta(indices['hy21']['maturity'])
hy21 = indices['hy21']
hy21["startdate"] = datetime.date(2013, 9, 20)
dates = [f[9:19] for f in os.listdir(os.path.join(os.environ['DATA_DIR'], "Backtest")) if "survprob" in f]
Rho = np.zeros((len(dates), 3))
for i, d in enumerate(dates):
startdate = datetime.datetime.strptime(d, "%Y-%m-%d")
ts = YC(startdate)
with open(os.path.join(os.environ['DATA_DIR'], "Backtest", "recov_{0}.csv".format(d))) as fh:
recov = np.array([float(e) for e in fh], dtype='double', order='F')
with open(os.path.join(os.environ['DATA_DIR'], "Backtest", "survprob_{0}.csv".format(d))) as fh:
fh.readline() ##skip header
SurvProb = np.array([[float(e) for e in line.split(",")] for line in fh], dtype='double', order='F')
defaultprob = 1 - SurvProb
issuerweights = np.ones(100)/100
rho = 0.4
Ngrid = 101
K = np.array([0, 0.15, 0.25, 0.35, 1])
Kmod = adjust_attachments(K, hy21["loss"], hy21["factor"])
quotes = pd.read_csv(os.path.join(os.environ['BASE_DIR'], "Scenarios", "Calibration",
"hy21_tranches_{0}.csv".format(d)))
quotes = quotes["Mid"]/100
dK = np.diff(Kmod)
quotes = np.cumsum(dK * (1-quotes))
sched = creditSchedule(startdate, "5Yr", 0.05, ts, enddate=hy21["maturity"])
acc = cdsAccrued(startdate, 0.05)
for j, q in enumerate(quotes[:-1]):
def aux(rho):
L, R = BClossdist(defaultprob, issuerweights, recov, rho, Z, w, 101)
cl = tranche_cl(L, R, sched, 0, Kmod[j+1])
pl = tranche_pl(L, sched, 0, Kmod[j+1])
return cl+pl+q-acc
l, u = (0, 1)
for _ in range(10):
rho = (l+u)/2.
if aux(rho) > 0:
u = rho
else:
l = rho
Rho[i, j] = (l+u)/2.
print(Rho[i,:])
|
