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-rw-r--r--python/analytics/curve_trades.py6
-rw-r--r--python/analytics/option.py11
-rw-r--r--python/analytics/portfolio.py6
-rw-r--r--python/analytics/sabr.py4
-rw-r--r--python/exploration/tranches.py2
-rw-r--r--python/tests/test_cds.py8
-rw-r--r--python/tests/test_index.py17
-rw-r--r--python/tests/test_scenarios.py18
-rw-r--r--python/tests/test_swaption.py21
9 files changed, 50 insertions, 43 deletions
diff --git a/python/analytics/curve_trades.py b/python/analytics/curve_trades.py
index f76f6b88..b989bd69 100644
--- a/python/analytics/curve_trades.py
+++ b/python/analytics/curve_trades.py
@@ -1,6 +1,6 @@
from analytics.index_data import get_index_quotes, index_returns
from db import dbengine
-from analytics import Index, Portfolio
+from analytics import CreditIndex, Portfolio
from analytics.utils import roll_date
from dateutil.relativedelta import relativedelta
from analytics.basket_index import MarkitBasketIndex
@@ -278,8 +278,8 @@ def curve_pos(value_date, index_type='IG'):
df = pd.read_sql_query(sql_string, dawndb,
params=[value_date, f'SER_{index_type}CURVE'])
- portf = Portfolio([Index.from_name(row.index, row.series, row.tenor,
- value_date, -row.notional)
+ portf = Portfolio([CreditIndex(row.index, row.series, row.tenor,
+ value_date, -row.notional)
for row in df[['index', 'tenor', 'series', 'notional']].
itertuples(index=False)])
portf.mark()
diff --git a/python/analytics/option.py b/python/analytics/option.py
index c0989814..34f1b7a0 100644
--- a/python/analytics/option.py
+++ b/python/analytics/option.py
@@ -8,7 +8,7 @@ from db import dbengine
from .black import black, Nx
from .sabr import sabr
from .utils import GHquad, build_table
-from .index import g, ForwardIndex, Index
+from .index import g, ForwardIndex, CreditIndex
from .db import _engine
from yieldcurve import roll_yc
from pandas.tseries.offsets import BDay
@@ -55,7 +55,7 @@ def ATMstrike(index, exercise_date):
Parameters
----------
index :
- Index object
+ CreditIndex object
exercise_date : datetime.date
expiration date.
price : bool, defaults to False
@@ -99,7 +99,7 @@ class BlackSwaption(ForwardIndex):
if rec is None:
return ValueError("trade_id doesn't exist")
if index is None:
- index = Index.from_name(redcode=rec.security_id, maturity=rec.maturity, value_date=rec.trade_date)
+ index = CreditIndex(redcode=rec.security_id, maturity=rec.maturity, value_date=rec.trade_date)
index.ref = rec.index_ref
instance = cls(index, rec.expiration_date, rec.strike, rec.swaption_type.lower(),
direction="Long" if rec.buysell else "Short")
@@ -519,6 +519,7 @@ class QuoteSurface():
r.append((quotedate, quotesource))
return r
+
class VolSurface(QuoteSurface):
def __init__(self, index_type, series, tenor='5yr', value_date=datetime.date.today()):
super().__init__(index_type, series, tenor, value_date)
@@ -626,7 +627,7 @@ class ModelBasedVolSurface(VolSurface):
def __init__(self, index_type, series, tenor='5yr', value_date=datetime.date.today(),
interp_method='bivariate_spline'):
super().__init__(index_type, series, tenor, value_date)
- self._index = Index.from_name(index_type, series, tenor, value_date, notional=1.)
+ self._index = CreditIndex(index_type, series, tenor, value_date, notional=1.)
self._surfaces = {}
self._index_refs = {}
self._quotes = self._quotes.assign(
@@ -716,7 +717,7 @@ class ProbSurface(QuoteSurface):
def __init__(self, index_type, series, tenor='5yr', value_date=datetime.date.today()):
super().__init__(index_type, series, tenor, value_date)
self._surfaces = {}
- self._index = Index.from_name(index_type, series, tenor, value_date)
+ self._index = CreditIndex(index_type, series, tenor, value_date)
def __getitem__(self, surface_id):
if surface_id not in self._surfaces:
diff --git a/python/analytics/portfolio.py b/python/analytics/portfolio.py
index 004288f2..3b9e1a9a 100644
--- a/python/analytics/portfolio.py
+++ b/python/analytics/portfolio.py
@@ -1,4 +1,4 @@
-from .index import Index
+from .index import CreditIndex
from .option import BlackSwaption
from warnings import warn
import pandas as pd
@@ -36,7 +36,7 @@ class Portfolio:
def __init__(self, trades, trade_ids=None):
self.trades = trades
self.trade_ids = trade_ids
- self.indices = [t for t in trades if isinstance(t, Index)]
+ self.indices = [t for t in trades if isinstance(t, CreditIndex)]
self.swaptions = [t for t in trades if isinstance(t, BlackSwaption)]
value_dates = set(t.value_date for t in self.trades)
self._keys = set([(index.index_type, index.series, index.tenor) for index in self.indices])
@@ -158,7 +158,7 @@ class Portfolio:
"Vega"]
rec = []
for t in self.trades:
- if isinstance(t, Index):
+ if isinstance(t, CreditIndex):
name = f"{t.index_type}{t.series} {t.tenor}"
r = ("Index", name,
t.notional, t.ref, "N/A", t.direction, "N/A", "N/A", None, t.pv, 1., 0., t.theta, 0.)
diff --git a/python/analytics/sabr.py b/python/analytics/sabr.py
index eba32bac..4de15338 100644
--- a/python/analytics/sabr.py
+++ b/python/analytics/sabr.py
@@ -58,10 +58,10 @@ def sabr(alpha, beta, rho, nu, F, K, T):
if __name__ == "__main__":
from analytics.option import BlackSwaption
- from analytics import Index
+ from analytics import CreditIndex
from scipy.optimize import least_squares
- underlying = Index.from_name("IG", 28, "5yr")
+ underlying = CreditIndex("IG", 28, "5yr")
underlying.spread = 67.5
exercise_date = datetime.date(2017, 9, 20)
option = BlackSwaption(underlying, exercise_date, 70)
diff --git a/python/exploration/tranches.py b/python/exploration/tranches.py
index a8e8d05e..0a5f969a 100644
--- a/python/exploration/tranches.py
+++ b/python/exploration/tranches.py
@@ -7,7 +7,7 @@ import analytics.basket_index as idx_bkt
import numpy as np
import pandas as pd
-from analytics import Swaption, BlackSwaption, Index, BlackSwaptionVolSurface, Portfolio, ProbSurface
+from analytics import Swaption, BlackSwaption, CreditIndex, BlackSwaptionVolSurface, Portfolio, ProbSurface
from analytics.scenarios import run_swaption_scenarios, run_index_scenarios, run_portfolio_scenarios, run_tranche_scenarios
from scipy.interpolate import interp1d
diff --git a/python/tests/test_cds.py b/python/tests/test_cds.py
index 44832dea..350f722a 100644
--- a/python/tests/test_cds.py
+++ b/python/tests/test_cds.py
@@ -10,12 +10,12 @@ from quantlib.time.api import Date
import sys
sys.path.append('..')
-from analytics import Index
+from analytics import CreditIndex
from yieldcurve import YC, ql_to_jp, get_curve
class TestUpfront(unittest.TestCase):
- index = Index.from_name("ig", 26, "5yr",
- value_date=datetime.date(2016, 9, 21))
+ index = CreditIndex("ig", 26, "5yr",
+ value_date=datetime.date(2016, 9, 21))
index.notional = 50e6
index.spread = 70
@@ -73,5 +73,5 @@ class TestSpreadCurve(unittest.TestCase):
b = cl.pv(trade_date, step_in_date, cash_settle_date, yc, sc, True)
self.assertAlmostEqual(a - b, upf)
-if __name__=="__main__":
+if __name__ == "__main__":
unittest.main()
diff --git a/python/tests/test_index.py b/python/tests/test_index.py
index 59dbfe88..d9dbf868 100644
--- a/python/tests/test_index.py
+++ b/python/tests/test_index.py
@@ -5,13 +5,13 @@ import numpy as np
from pyisda.cdsone import upfront_charge
from pyisda.flat_hazard import pv_vec
-from analytics import Index, ForwardIndex
+from analytics import CreditIndex, ForwardIndex
from analytics.index import g
import pickle
+
class TestPickle(unittest.TestCase):
- index = Index.from_name("ig", 26, "5yr",
- value_date=datetime.date(2016, 7, 1))
+ index = CreditIndex("ig", 26, "5yr", value_date=datetime.date(2016, 7, 1))
index.notional = 50e6
index.spread = 75
@@ -19,9 +19,9 @@ class TestPickle(unittest.TestCase):
a = pickle.loads(pickle.dumps(self.index))
self.assertTrue(hash(a) == hash(self.index))
+
class TestStrike(unittest.TestCase):
- index = Index.from_name("ig", 26, "5yr",
- value_date=datetime.date(2016, 7, 1))
+ index = CreditIndex("ig", 26, "5yr", value_date=datetime.date(2016, 7, 1))
index.notional = 50_000_000.
index.spread = 75
exercise_date = datetime.date(2016, 8, 19)
@@ -55,9 +55,10 @@ class TestStrike(unittest.TestCase):
self.index.price = self.index.price
self.assertAlmostEqual(self.index.spread, 75)
+
class TestForwardIndex(unittest.TestCase):
- index = Index.from_name("ig", 26, "5yr",
- value_date=datetime.date(2016, 7, 1))
+ index = CreditIndex("ig", 26, "5yr",
+ value_date=datetime.date(2016, 7, 1))
index.notional = 50_000_000.
index.spread = 75
exercise_date = datetime.date(2016, 8, 19)
@@ -74,5 +75,5 @@ class TestForwardIndex(unittest.TestCase):
fi = ForwardIndex(self.index, self.index.value_date)
self.assertAlmostEqual(fi.forward_pv, self.index.clean_pv / self.index.notional)
-if __name__=="__main__":
+if __name__ == "__main__":
unittest.main()
diff --git a/python/tests/test_scenarios.py b/python/tests/test_scenarios.py
index d079b1c9..c22c8be3 100644
--- a/python/tests/test_scenarios.py
+++ b/python/tests/test_scenarios.py
@@ -1,18 +1,20 @@
import unittest
-import datetime
import numpy as np
import pandas as pd
-from analytics import Index, BlackSwaption, Portfolio, BlackSwaptionVolSurface
+from analytics import CreditIndex, BlackSwaption, Portfolio, BlackSwaptionVolSurface
from pandas.tseries.offsets import BDay
-from analytics.scenarios import run_portfolio_scenarios, run_swaption_scenarios, run_index_scenarios
+from analytics.scenarios import (run_portfolio_scenarios,
+ run_swaption_scenarios, run_index_scenarios)
+
class TestSenarios(unittest.TestCase):
- option_delta = Index.from_tradeid(874)
+ option_delta = CreditIndex.from_tradeid(874)
option1 = BlackSwaption.from_tradeid(7, option_delta)
option2 = BlackSwaption.from_tradeid(8, option_delta)
portf = Portfolio([option1, option2, option_delta])
- date_range = pd.bdate_range(option_delta.value_date, pd.Timestamp('2017-05-17') - BDay(), freq = '5B')
+ date_range = pd.bdate_range(option_delta.value_date,
+ pd.Timestamp('2017-05-17') - BDay(), freq='5B')
def test_portfolio(self):
""" check that run_portfolio_scenarios match the sum of the individual pieces"""
@@ -21,7 +23,9 @@ class TestSenarios(unittest.TestCase):
vs = BlackSwaptionVolSurface("IG", 28, value_date=self.option_delta.value_date)
vol_surface = vs[vs.list(source="BAML")[-1]]
df = run_portfolio_scenarios(self.portf, self.date_range,
- spread_shock, vol_shock, vol_surface)
+ spread_shock=spread_shock,
+ vol_shock=vol_shock,
+ vol_surface=vol_surface)
df = df.set_index(['spread', 'vol_shock'], append=True)
df1 = run_swaption_scenarios(self.option1, self.date_range,
@@ -38,5 +42,5 @@ class TestSenarios(unittest.TestCase):
df_orig = df_orig.set_index('vol_shock', append=True)
self.assertFalse(np.any((df-df_orig).values))
-if __name__=="__main__":
+if __name__ == "__main__":
unittest.main()
diff --git a/python/tests/test_swaption.py b/python/tests/test_swaption.py
index c270dd2d..4faea8fe 100644
--- a/python/tests/test_swaption.py
+++ b/python/tests/test_swaption.py
@@ -4,11 +4,12 @@ import datetime
import sys
sys.path.append('..')
from analytics.index import g
-from analytics import Index, Swaption, BlackSwaption
+from analytics import CreditIndex, Swaption, BlackSwaption
+
class TestPutCallParity(unittest.TestCase):
- index = Index.from_name("ig", 27, "5yr",
- value_date= datetime.date(2016, 10, 25))
+ index = CreditIndex("ig", 27, "5yr",
+ value_date= datetime.date(2016, 10, 25))
index.spread = 74
exercise_date = datetime.date(2017, 3, 15)
strike = 82.5
@@ -42,8 +43,8 @@ class TestPutCallParity(unittest.TestCase):
self.assertAlmostEqual(payer.sigma, 0.37648716)
def test_hy(self):
- index = Index.from_name("hy", 27, "5yr",
- value_date=datetime.date(2016, 11, 8))
+ index = CreditIndex("hy", 27, "5yr",
+ value_date=datetime.date(2016, 11, 8))
index.price = 103.875
exercise_date = datetime.date(2017, 3, 15)
strike = 102.5
@@ -54,13 +55,13 @@ class TestPutCallParity(unittest.TestCase):
class TestBreakeven(unittest.TestCase):
exercise_date = datetime.date(2017, 3, 15)
- hyindex = Index.from_name("hy", 27, "5yr",
- value_date=datetime.date(2016, 11, 16))
+ hyindex = CreditIndex("hy", 27, "5yr",
+ value_date=datetime.date(2016, 11, 16))
hyindex.price = 103.75
hystrike = 102.5
- igindex = Index.from_name("ig", 27, "5yr",
- value_date=datetime.date(2016, 11, 18))
+ igindex = CreditIndex("ig", 27, "5yr",
+ value_date=datetime.date(2016, 11, 18))
igindex.spread = 76.5
igstrike = 80
@@ -90,5 +91,5 @@ class TestBreakeven(unittest.TestCase):
receiver.notional = 1e7
self.assertAlmostEqual(receiver.breakeven, 73.715942707132982)
-if __name__=="__main__":
+if __name__ == "__main__":
unittest.main()
generated by cgit v1.2.3-70-g09d2 (git 2.52.0) at 2025-12-21 20:57:07 +0000