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
63
64
65
66
67
68
69
70
71
72
73
74
|
from common import root
import os
import requests, zipfile
from io import BytesIO
import xml.etree.ElementTree as ET
import datetime
from quantlib.time.api import Calendar, Date, Period, Days, Schedule, today
from quantlib.time import imm
from quantlib.util.converter import qldate_to_pydate, pydate_to_qldate
from quantlib.market.market import libor_market
import numpy as np
import matplotlib.pyplot as plt
def getMarkitIRData(date = datetime.date.today()):
basedir = os.path.join(root, "data", "Yield Curves")
datestr = datetime.datetime.strftime(date, "%Y%m%d")
filename = "InterestRates_USD_{0}.xml".format(datestr)
if not os.path.exists(os.path.join(basedir, filename)):
r = requests.get('http://www.markit.com/news/InterestRates_USD_{0}.zip'.format(datestr))
if "x-zip" in r.headers['content-type']:
with zipfile.ZipFile(BytesIO(r.content)) as z:
z.extractall(path = os.path.join(root, "data", "Yield Curves"))
else:
return getMarkitIRData(date-datetime.timedelta(days=1))
tree = ET.parse(os.path.join(root, "data", "Yield Curves", filename))
deposits = {tenor: rate for tenor, rate in \
zip([e.text for e in tree.findall('./deposits/*/tenor')],
[float(e.text) for e in tree.findall('./deposits/*/parrate')])}
swaps = {tenor: rate for tenor, rate in \
zip([e.text for e in tree.findall('./swaps/*/tenor')],
[float(e.text) for e in tree.findall('./swaps/*/parrate')])}
effectiveasof = tree.find('./effectiveasof').text
MarkitData = {'deposits': deposits,
'swaps': swaps,
'effectiveasof': datetime.datetime.strptime(effectiveasof, "%Y-%m-%d").date()}
return MarkitData
def get_futures_data(date = datetime.date.today()):
futures_file = os.path.join(root, "data", "Yield Curves",
"futures-{0}.csv".format(str(date)))
with open(futures_file) as fh:
quotes = [float(line.split(",")[1]) for line in fh]
return quotes
def YC(date = datetime.date.today(), MarkitData=None, futures = None):
if not MarkitData:
MarkitData = getMarkitIRData(date)
if not futures:
calendar = Calendar.from_name('TARGET')## need to figure out which is the right calendar to use
prev_day = calendar.advance(pydate_to_qldate(date), -1, Days)
futures = get_futures_data(qldate_to_pydate(prev_day).date())
m = libor_market('USD(NY)')
quotes = [('ED',i+1, v) for i, v in enumerate(futures)]
quotes += [('SWAP', k, v) for k, v in MarkitData['swaps'].items()]
m.set_quotes(date, quotes)
m.bootstrap_term_structure()
return m
if __name__=="__main__":
m = YC()
p1 = Period('1Mo')
p2 = Period('2Mo')
p3 = Period('3Mo')
p6 = Period('6Mo')
p12 = Period('12Mo')
calendar = Calendar.from_name(m.calendar)
sched = Schedule(m.settle_date, m.settle_date+Period('5Yr'), Period('3Mo'), calendar)
days = [qldate_to_pydate(day) for day in sched]
f3 = [m.forward(d, p3, 1) for d in sched]
f6 = [m.forward(d, p6, 1) for d in sched]
f2 = [m.forward(d, p2, 1) for d in sched]
plt.plot(days, f2, days, f3, days, f6)
plt.show()
|
