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import unittest
import numpy as np
import pandas as pd
from serenitas.analytics.api import (
CreditIndex,
BlackSwaption,
Portfolio,
BlackSwaptionVolSurface,
)
from pandas.tseries.offsets import BDay
from serenitas.analytics.scenarios import (
run_portfolio_scenarios,
run_swaption_scenarios,
run_index_scenarios,
)
class TestSenarios(unittest.TestCase):
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], trade_ids=["opt1", "opt2", "delta"]
)
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"""
vol_shock = np.arange(-0.15, 0.3, 0.01)
spread_shock = np.arange(-0.2, 0.3, 0.01)
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=spread_shock,
vol_shock=vol_shock,
vol_surface=vol_surface,
)
df1 = run_swaption_scenarios(
self.option1, self.date_range, spread_shock, vol_shock, vol_surface, ["pnl"]
)
df2 = run_swaption_scenarios(
self.option2, self.date_range, spread_shock, vol_shock, vol_surface, ["pnl"]
)
df_index = run_index_scenarios(self.option_delta, self.date_range, spread_shock)
df_swaptions = df1 + df2
df_swaptions = df_swaptions.reset_index(level="vol_shock")
df_orig = df_index.add(df_swaptions, fill_value=0)
df_orig = df_orig.set_index("vol_shock", append=True)
self.assertFalse(np.any((df.sum(axis=1).values - df_orig["pnl"].values)))
if __name__ == "__main__":
unittest.main()
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