def test_backtothefuture_pricing(mocker):
with MockCalc(mocker):
swap1 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.01, name='swap1')
swap2 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.02, name='swap2')
swap3 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.03, name='swap3')
portfolio = Portfolio((swap1, swap2, swap3))
pricing_date = dt.date(2021, 2, 10)
with PricingContext(pricing_date=pricing_date):
with BackToTheFuturePricingContext(dates=business_day_offset(
pricing_date, [-1, 0, 1], roll='forward')) as hpc:
risk_key = hpc._PricingContext__risk_key(
risk.DollarPrice, swap1.provider)
results = portfolio.calc(risk.DollarPrice)
expected = risk.SeriesWithInfo(
pd.Series(
data=[-22711963.80864744, -22655907.930484552, -21582551.58922608],
index=business_day_offset(pricing_date, [-1, 0, 1],
roll='forward')),
risk_key=historical_risk_key(risk_key),
)
actual = results[risk.DollarPrice].aggregate()
assert actual.equals(expected)
def test_backtothefuture_pricing(mocker):
with MockCalc(mocker):
swap1 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.01, name='swap1')
swap2 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.02, name='swap2')
swap3 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.03, name='swap3')
portfolio = Portfolio((swap1, swap2, swap3))
pricing_date = dt.date(2020, 10, 7)
with PricingContext(pricing_date=pricing_date):
with BackToTheFuturePricingContext(dates=business_day_offset(
pricing_date, [-1, 0, 1], roll='forward')) as hpc:
risk_key = hpc._PricingContext__risk_key(
risk.DollarPrice, swap1.provider)
results = portfolio.calc(risk.DollarPrice)
expected = risk.SeriesWithInfo(
pd.Series(
data=[-35280379.86540368, -35348910.76427929, -30830994.939595155],
index=business_day_offset(pricing_date, [-1, 0, 1],
roll='forward')),
risk_key=risk_key.ex_date_and_market,
)
actual = results[risk.DollarPrice].aggregate()
assert actual.equals(expected)
def test_historical_pricing(mocker):
with MockCalc(mocker):
swap1 = IRSwap('Pay', '10y', 'USD', fixed_rate='ATM+1', name='10y@a+1')
swap2 = IRSwap('Pay', '10y', 'USD', fixed_rate='ATM+2', name='10y@a+2')
swap3 = IRSwap('Pay', '10y', 'USD', fixed_rate='ATM+3', name='10y@a+3')
portfolio = Portfolio((swap1, swap2, swap3))
dates = (dt.date(2021, 2, 9), dt.date(2021, 2, 10), dt.date(2021, 2, 11))
with HistoricalPricingContext(dates=dates) as hpc:
risk_key = hpc._PricingContext__risk_key(risk.DollarPrice, swap1.provider)
results = portfolio.calc((risk.DollarPrice, risk.IRDelta))
expected = risk.SeriesWithInfo(
pd.Series(
data=[-580316.7895084377, -580373.4091600645, -580811.1441974249],
index=[dt.date(2021, 2, 9), dt.date(2021, 2, 10), dt.date(2021, 2, 11)]
),
risk_key=historical_risk_key(risk_key), )
assert results.dates == dates
actual = results[risk.DollarPrice].aggregate()
assert actual.equals(expected)
assert (results[dt.date(2021, 2, 9)][risk.DollarPrice]['10y@a+1'] ==
results[risk.DollarPrice][dt.date(2021, 2, 9)]['10y@a+1'])
assert (results[dt.date(2021, 2, 9)][risk.DollarPrice]['10y@a+1'] ==
results[risk.DollarPrice]['10y@a+1'][dt.date(2021, 2, 9)])
assert (results[dt.date(2021, 2, 9)][risk.DollarPrice]['10y@a+1'] ==
results['10y@a+1'][risk.DollarPrice][dt.date(2021, 2, 9)])
assert (results[dt.date(2021, 2, 9)][risk.DollarPrice]['10y@a+1'] ==
results['10y@a+1'][dt.date(2021, 2, 9)][risk.DollarPrice])
assert (results[dt.date(2021, 2, 9)][risk.DollarPrice]['10y@a+1'] ==
results[dt.date(2021, 2, 9)]['10y@a+1'][risk.DollarPrice])
def test_backtothefuture_pricing(mocker):
set_session()
day1 = [
[
[{'$type': 'Risk', 'val': 0.01}],
[{'$type': 'Risk', 'val': 0.02}],
[{'$type': 'Risk', 'val': 0.03}],
]
]
day2 = [
[
[{'$type': 'Risk', 'val': 0.011}],
[{'$type': 'Risk', 'val': 0.021}],
[{'$type': 'Risk', 'val': 0.031}],
]
]
day3 = [
[
[{'$type': 'Risk', 'val': 0.012}],
[{'$type': 'Risk', 'val': 0.022}],
[{'$type': 'Risk', 'val': 0.032}],
]
]
mocker.return_value = [day1, day2, day3]
swap1 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.01, name='swap1')
swap2 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.02, name='swap2')
swap3 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.03, name='swap3')
portfolio = Portfolio((swap1, swap2, swap3))
with BackToTheFuturePricingContext(dates=business_day_offset(dt.datetime.today().date(), [-1, 0, 1],
roll='forward')) as hpc:
risk_key = hpc._PricingContext__risk_key(risk.DollarPrice, swap1.provider)
results = portfolio.calc(risk.DollarPrice)
expected = risk.SeriesWithInfo(
pd.Series(
data=[0.06, 0.063, 0.066],
index=business_day_offset(dt.datetime.today().date(), [-1, 0, 1], roll='forward')
),
risk_key=risk_key.ex_date_and_market,)
actual = results[risk.DollarPrice].aggregate()
assert actual.equals(expected)
def test_historical_pricing(mocker):
with MockCalc(mocker):
swap1 = IRSwap('Pay', '10y', 'USD', fixed_rate='ATM+1', name='10y@a+1')
swap2 = IRSwap('Pay', '10y', 'USD', fixed_rate='ATM+2', name='10y@a+2')
swap3 = IRSwap('Pay', '10y', 'USD', fixed_rate='ATM+3', name='10y@a+3')
portfolio = Portfolio((swap1, swap2, swap3))
dates = (dt.date(2019, 10, 7), dt.date(2019, 10,
8), dt.date(2019, 10, 9))
with HistoricalPricingContext(dates=dates) as hpc:
risk_key = hpc._PricingContext__risk_key(risk.DollarPrice,
swap1.provider)
results = portfolio.calc((risk.DollarPrice, risk.IRDelta))
expected = risk.SeriesWithInfo(
pd.Series(data=[
-564854.3640043903, -565604.2636791412, -564751.5121349357
],
index=[
dt.date(2019, 10, 7),
dt.date(2019, 10, 8),
dt.date(2019, 10, 9)
]),
risk_key=risk_key.ex_date_and_market,
)
assert results.dates == dates
actual = results[risk.DollarPrice].aggregate()
assert actual.equals(expected)
assert (results[dt.date(2019, 10, 9)][risk.DollarPrice]['10y@a+1'] ==
results[risk.DollarPrice][dt.date(2019, 10, 9)]['10y@a+1'])
assert (results[dt.date(2019, 10, 9)][risk.DollarPrice]['10y@a+1'] ==
results[risk.DollarPrice]['10y@a+1'][dt.date(2019, 10, 9)])
assert (results[dt.date(2019, 10, 9)][risk.DollarPrice]['10y@a+1'] ==
results['10y@a+1'][risk.DollarPrice][dt.date(2019, 10, 9)])
assert (results[dt.date(
2019, 10,
9)][risk.DollarPrice]['10y@a+1'] == results['10y@a+1'][dt.date(
2019, 10, 9)][risk.DollarPrice])
assert (results[dt.date(
2019, 10, 9)][risk.DollarPrice]['10y@a+1'] == results[dt.date(
2019, 10, 9)]['10y@a+1'][risk.DollarPrice])
def test_historical_pricing(mocker):
set_session()
dollar_price_ir_delta_values = [[[{
'$type': 'Risk',
'val': 0.01
}, {
'$type': 'Risk',
'val': 0.011
}, {
'$type': 'Risk',
'val': 0.012
}],
[{
'$type': 'Risk',
'val': 0.02
}, {
'$type': 'Risk',
'val': 0.021
}, {
'$type': 'Risk',
'val': 0.022
}],
[{
'$type': 'Risk',
'val': 0.03
}, {
'$type': 'Risk',
'val': 0.031
}, {
'$type': 'Risk',
'val': 0.032
}]],
[[{
'$type':
'RiskVector',
'asset': [0.01, 0.015],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}, {
'$type':
'RiskVector',
'asset': [0.011, 0.0151],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}, {
'$type':
'RiskVector',
'asset': [0.012, 0.0152],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}],
[{
'$type':
'RiskVector',
'asset': [0.02, 0.025],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}, {
'$type':
'RiskVector',
'asset': [0.021, 0.0251],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}, {
'$type':
'RiskVector',
'asset': [0.022, 0.0252],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}],
[{
'$type':
'RiskVector',
'asset': [0.03, 0.035],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}, {
'$type':
'RiskVector',
'asset': [0.031, 0.0351],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}, {
'$type':
'RiskVector',
'asset': [0.032, 0.0352],
'points': [{
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '1y'
}, {
'type': 'IR',
'asset': 'USD',
'class_': 'Swap',
'point': '2y'
}]
}]]]
mocker.return_value = [dollar_price_ir_delta_values]
swap1 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.01, name='swap1')
swap2 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.02, name='swap2')
swap3 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.03, name='swap3')
portfolio = Portfolio((swap1, swap2, swap3))
with HistoricalPricingContext(dates=(dt.date(2019, 10, 7),
dt.date(2019, 10, 8),
dt.date(2019, 10, 9))) as hpc:
risk_key = hpc._PricingContext__risk_key(risk.DollarPrice,
swap1.provider())
results = portfolio.calc((risk.DollarPrice, risk.IRDelta))
expected = risk.SeriesWithInfo(
pd.Series(data=[0.06, 0.063, 0.066],
index=[
dt.date(2019, 10, 7),
dt.date(2019, 10, 8),
dt.date(2019, 10, 9)
]),
risk_key=risk_key.base,
)
actual = results[risk.DollarPrice].aggregate()
assert actual.equals(expected)
def test_historical_pricing(mocker):
set_session()
dollar_price_ir_delta_values = [
[
[
{'date': '2019-10-07', 'value': 0.01},
{'date': '2019-10-08', 'value': 0.011},
{'date': '2019-10-09', 'value': 0.012}
],
[
{'date': '2019-10-07', 'value': 0.02},
{'date': '2019-10-08', 'value': 0.021},
{'date': '2019-10-09', 'value': 0.022}
],
[
{'date': '2019-10-07', 'value': 0.03},
{'date': '2019-10-08', 'value': 0.031},
{'date': '2019-10-09', 'value': 0.032}
]
],
[
[
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.01},
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.015},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.011},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.0151},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.012},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.0152}
],
[
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.02},
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.025},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.021},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.0251},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.022},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.0252}
],
[
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.03},
{'date': '2019-10-07', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.035},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.031},
{'date': '2019-10-08', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.0351},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '1y', 'value': 0.032},
{'date': '2019-10-09', 'marketDataType': 'IR', 'assetId': 'USD', 'pointClass': 'Swap',
'point': '2y', 'value': 0.0352}
]
]
]
mocker.return_value = dollar_price_ir_delta_values
swap1 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.01, name='swap1')
swap2 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.02, name='swap2')
swap3 = IRSwap('Pay', '10y', 'USD', fixed_rate=0.03, name='swap3')
portfolio = Portfolio((swap1, swap2, swap3))
with HistoricalPricingContext(dates=(dt.date(2019, 10, 7), dt.date(2019, 10, 8), dt.date(2019, 10, 9))) as hpc:
pricing_key = hpc.pricing_key
results = portfolio.calc((risk.DollarPrice, risk.IRDelta))
expected = risk.SeriesWithInfo(
pricing_key,
pd.Series(
data=[0.06, 0.063, 0.066],
index=[dt.date(2019, 10, 7), dt.date(2019, 10, 8), dt.date(2019, 10, 9)]
))
actual = results[risk.DollarPrice].aggregate()
assert actual.equals(expected)
