Portfolios

from gs_quant.session import Environment, GsSession
from gs_quant.common import PayReceive
from gs_quant.instrument import IRSwaption
import gs_quant.risk as risk
import datetime as dt

swaption1 = IRSwaption(PayReceive.Receive, '5y', 'EUR',
                       expiration_date='3m', name='EUR3m5y')
swaption2 = IRSwaption(PayReceive.Receive, '5y', 'EUR',
                       expiration_date='6m', name='EUR6m5y')

# Create Portfolio w/ swaptions
from gs_quant.markets.portfolio import Portfolio
portfolio = Portfolio((swaption1, swaption2))
portfolio.resolve()

# Calculate Risk for Portfolio
port_risk = portfolio.calc(
    (risk.DollarPrice, risk.IRDeltaParallel, risk.IRVega))

# View Instrument Level risk for portfolio
port_risk[risk.IRDeltaParallel]['EUR3m5y']

# View Aggregated Risk for a Portfolio
port_risk[risk.IRDeltaParallel].aggregate()

# Calculate Portfolio Risks within HistoricalPricingContext
from gs_quant.markets import HistoricalPricingContext

start_date = dt.date(2019, 6, 3)
end_date = dt.date(2019, 11, 18)

with HistoricalPricingContext(start_date, end_date):
    port_ird_res = portfolio.calc(risk.IRDeltaParallelLocalCcy)

port_ird_agg = port_ird_res[risk.IRDeltaParallelLocalCcy].aggregate()
swap1_ird = port_ird_res[risk.IRDeltaParallelLocalCcy]['EUR3m5y']
swap2_ird = port_ird_res[risk.IRDeltaParallelLocalCcy]['EUR6m5y']

import matplotlib.pyplot as plt

plt.figure(figsize=(7, 5))
plt.xlabel('Date')

ax1 = port_ird_agg.plot(label='Portfolio')
swap1_ird.plot(label='EUR3m5y')
swap2_ird.plot(label='EYR6m5y')
h1, l1 = ax1.get_legend_handles_labels()
plt.title('IRDeltaParallel Timeseries')
plt.legend(h1, l1, loc=2)
plt.show()