def generate_libor_observables(
start,
end,
roll_period=6,
roll_duration=ppf.date_time.months,
reset_period=6,
reset_duration=ppf.date_time.months,
tenor_period=6,
tenor_duration=ppf.date_time.months,
reset_currency="USD",
reset_basis=ppf.date_time.basis_act_360,
reset_holiday_centres=None,
reset_shift_method=ppf.date_time.shift_convention.modified_following,
reset_lag=0,
*arguments,
**keywords):
'''Generate a sequence of libor rates.
>>> from ppf.date_time import *
>>> observables = generate_libor_observables(
... start = date(2007, Jun, 29)
... , end = date(2012, Jun, 29)
... , roll_period = 6
... , roll_duration = ppf.date_time.months
... , reset_period = 3
... , reset_duration = ppf.date_time.months
... , tenor_period = 3
... , tenor_duration = ppf.date_time.months
... , reset_currency = "JPY"
... , reset_basis = basis_act_360
... , reset_shift_method = shift_convention.modified_following)
>>> for obs_per_flow in observables:
... for obs in obs_per_flow:
... print obs
0, 0, JPY, [2007-Jun-29, 2007-Sep-28], basis_act_360,
0, 1, JPY, [2007-Sep-28, 2007-Dec-31], basis_act_360,
1, 0, JPY, [2007-Dec-31, 2008-Mar-31], basis_act_360,
1, 1, JPY, [2008-Mar-31, 2008-Jun-30], basis_act_360,
2, 0, JPY, [2008-Jun-30, 2008-Sep-29], basis_act_360,
2, 1, JPY, [2008-Sep-29, 2008-Dec-29], basis_act_360,
3, 0, JPY, [2008-Dec-29, 2009-Mar-30], basis_act_360,
3, 1, JPY, [2009-Mar-30, 2009-Jun-29], basis_act_360,
4, 0, JPY, [2009-Jun-29, 2009-Sep-29], basis_act_360,
4, 1, JPY, [2009-Sep-29, 2009-Dec-29], basis_act_360,
5, 0, JPY, [2009-Dec-29, 2010-Mar-29], basis_act_360,
5, 1, JPY, [2010-Mar-29, 2010-Jun-29], basis_act_360,
6, 0, JPY, [2010-Jun-29, 2010-Sep-29], basis_act_360,
6, 1, JPY, [2010-Sep-29, 2010-Dec-29], basis_act_360,
7, 0, JPY, [2010-Dec-29, 2011-Mar-29], basis_act_360,
7, 1, JPY, [2011-Mar-29, 2011-Jun-29], basis_act_360,
8, 0, JPY, [2011-Jun-29, 2011-Sep-29], basis_act_360,
8, 1, JPY, [2011-Sep-29, 2011-Dec-29], basis_act_360,
9, 0, JPY, [2011-Dec-29, 2012-Mar-29], basis_act_360,
9, 1, JPY, [2012-Mar-29, 2012-Jun-29], basis_act_360,
'''
from ppf.date_time import days
shift = ppf.date_time.shift
if reset_lag > 0:
raise RuntimeError("index lag expected less or equal to zero")
day, flow_id, all_observables = 0, 0, []
while day < end:
roll_start = start + roll_duration(flow_id * roll_period)
roll_end = start + roll_duration((flow_id + 1) * roll_period)
reset_id = 0
proj_roll = roll_start
observables = []
while proj_roll < roll_end:
proj_start = shift(proj_roll, reset_shift_method,
reset_holiday_centres)
proj_end = shift(proj_roll + tenor_duration(tenor_period),
reset_shift_method, reset_holiday_centres)
reset_date = shift(proj_start + days(reset_lag),
reset_shift_method, reset_holiday_centres)
observables.append(
libor_rate(None, flow_id, reset_id, reset_date, reset_currency,
proj_start, proj_end, reset_basis, fixing(False)))
reset_id += 1
proj_roll = roll_start + reset_duration(reset_id * reset_period)
day = roll_end
all_observables.append(observables)
flow_id += 1
return all_observables
def generate_libor_observables(
start
, end
, roll_period = 6
, roll_duration = ppf.date_time.months
, reset_period = 6
, reset_duration = ppf.date_time.months
, tenor_period = 6
, tenor_duration = ppf.date_time.months
, reset_currency = "USD"
, reset_basis = ppf.date_time.basis_act_360
, reset_holiday_centres = None
, reset_shift_method = ppf.date_time.shift_convention.modified_following
, reset_lag = 0
, *arguments
, **keywords):
'''Generate a sequence of libor rates.
>>> from ppf.date_time import *
>>> observables = generate_libor_observables(
... start = date(2007, Jun, 29)
... , end = date(2012, Jun, 29)
... , roll_period = 6
... , roll_duration = ppf.date_time.months
... , reset_period = 3
... , reset_duration = ppf.date_time.months
... , tenor_period = 3
... , tenor_duration = ppf.date_time.months
... , reset_currency = "JPY"
... , reset_basis = basis_act_360
... , reset_shift_method = shift_convention.modified_following)
>>> for obs_per_flow in observables:
... for obs in obs_per_flow:
... print obs
0, 0, JPY, [2007-Jun-29, 2007-Sep-28], basis_act_360,
0, 1, JPY, [2007-Sep-28, 2007-Dec-31], basis_act_360,
1, 0, JPY, [2007-Dec-31, 2008-Mar-31], basis_act_360,
1, 1, JPY, [2008-Mar-31, 2008-Jun-30], basis_act_360,
2, 0, JPY, [2008-Jun-30, 2008-Sep-29], basis_act_360,
2, 1, JPY, [2008-Sep-29, 2008-Dec-29], basis_act_360,
3, 0, JPY, [2008-Dec-29, 2009-Mar-30], basis_act_360,
3, 1, JPY, [2009-Mar-30, 2009-Jun-29], basis_act_360,
4, 0, JPY, [2009-Jun-29, 2009-Sep-29], basis_act_360,
4, 1, JPY, [2009-Sep-29, 2009-Dec-29], basis_act_360,
5, 0, JPY, [2009-Dec-29, 2010-Mar-29], basis_act_360,
5, 1, JPY, [2010-Mar-29, 2010-Jun-29], basis_act_360,
6, 0, JPY, [2010-Jun-29, 2010-Sep-29], basis_act_360,
6, 1, JPY, [2010-Sep-29, 2010-Dec-29], basis_act_360,
7, 0, JPY, [2010-Dec-29, 2011-Mar-29], basis_act_360,
7, 1, JPY, [2011-Mar-29, 2011-Jun-29], basis_act_360,
8, 0, JPY, [2011-Jun-29, 2011-Sep-29], basis_act_360,
8, 1, JPY, [2011-Sep-29, 2011-Dec-29], basis_act_360,
9, 0, JPY, [2011-Dec-29, 2012-Mar-29], basis_act_360,
9, 1, JPY, [2012-Mar-29, 2012-Jun-29], basis_act_360,
'''
from ppf.date_time import days
shift = ppf.date_time.shift
if reset_lag > 0:
raise RuntimeError ("index lag expected less or equal to zero")
day, flow_id, all_observables = 0, 0, []
while day < end:
roll_start = start + roll_duration(flow_id*roll_period)
roll_end = start + roll_duration((flow_id+1)*roll_period)
reset_id = 0
proj_roll = roll_start
observables = []
while proj_roll < roll_end:
proj_start = shift(
proj_roll
, reset_shift_method, reset_holiday_centres)
proj_end = shift(
proj_roll+tenor_duration(tenor_period)
, reset_shift_method, reset_holiday_centres)
reset_date = shift(
proj_start+days(reset_lag)
, reset_shift_method, reset_holiday_centres)
observables.append(
libor_rate(None, flow_id, reset_id, reset_date
, reset_currency, proj_start, proj_end
, reset_basis, fixing(False)))
reset_id += 1
proj_roll = roll_start+reset_duration(reset_id*reset_period)
day = roll_end
all_observables.append(observables)
flow_id += 1
return all_observables
def generate_swap_observables(
start,
end,
attributes,
spread=0,
roll_period=6,
roll_duration=ppf.date_time.months,
tenor_period=10,
tenor_duration=ppf.date_time.years,
reset_currency="USD",
reset_basis=ppf.date_time.basis_act_360,
reset_holiday_centres=None,
reset_shift_method=ppf.date_time.shift_convention.modified_following,
reset_lag=0,
*arguments,
**keywords):
'''Generate a sequence of swap rates.
>>> from ppf.date_time import *
>>> props = {}
>>> props["fixed-pay-period"] = 1
>>> props["fixed-pay-period-duration"] = years
>>> props["fixed-pay-basis"] = basis_act_360
>>> props["fixed-pay-holiday-centers"] = None
>>> props["fixed-shift-convention"] = modified_following
>>> props["float-pay-period"] = 6
>>> props["float-pay-period-duration"] = months
>>> props["float-pay-basis"] = basis_act_365
>>> props["float-pay-holiday-centers"] = None
>>> props["float-shift-convention"] = modified_following
>>> props["index-basis"] = basis_act_365
>>> props["index-holiday-centers"] = None
>>> props["index-shift-convention"] = modified_following
>>> observables = generate_swap_observables(
... start = date(2007, Jun, 29)
... , end = date(2017, Jun, 29)
... , attributes = props
... , roll_period = 1
... , roll_duration = years
... , tenor_period = 10
... , tenor_duration = years)
>>> for o in observables: print o
0, 0, USD, [2007-Jun-29, 2017-Jun-29],
1, 0, USD, [2008-Jun-30, 2018-Jun-29],
2, 0, USD, [2009-Jun-29, 2019-Jun-28],
3, 0, USD, [2010-Jun-29, 2020-Jun-29],
4, 0, USD, [2011-Jun-29, 2021-Jun-29],
5, 0, USD, [2012-Jun-29, 2022-Jun-29],
6, 0, USD, [2013-Jun-28, 2023-Jun-29],
7, 0, USD, [2014-Jun-30, 2024-Jun-28],
8, 0, USD, [2015-Jun-29, 2025-Jun-30],
9, 0, USD, [2016-Jun-29, 2026-Jun-29],
'''
from ppf.date_time import days
shift = ppf.date_time.shift
if reset_lag > 0:
raise RuntimeError("index lag expected less or equal to zero")
day, flow_id, all_observables = 0, 0, []
while day < end:
roll_start = start + roll_duration(flow_id * roll_period)
roll_end = start + roll_duration((flow_id + 1) * roll_period)
reset_id = 0
proj_roll = roll_start
proj_start = \
shift(
proj_roll
, reset_shift_method
, reset_holiday_centres
)
proj_end = \
shift(
proj_roll+tenor_duration(tenor_period)
, reset_shift_method, reset_holiday_centres
)
reset_date = \
shift(
proj_start+days(reset_lag)
, reset_shift_method, reset_holiday_centres
)
all_observables.append(
swap_rate(attributes, flow_id, reset_id,
reset_date, reset_currency, proj_start, proj_end,
fixing(False), spread))
flow_id += 1
reset_id += 1
day = roll_end
return all_observables
def generate_swap_observables(
start
, end
, attributes
, spread = 0
, roll_period = 6
, roll_duration = ppf.date_time.months
, tenor_period = 10
, tenor_duration = ppf.date_time.years
, reset_currency = "USD"
, reset_basis = ppf.date_time.basis_act_360
, reset_holiday_centres = None
, reset_shift_method = ppf.date_time.shift_convention.modified_following
, reset_lag = 0
, *arguments
, **keywords):
'''Generate a sequence of swap rates.
>>> from ppf.date_time import *
>>> props = {}
>>> props["fixed-pay-period"] = 1
>>> props["fixed-pay-period-duration"] = years
>>> props["fixed-pay-basis"] = basis_act_360
>>> props["fixed-pay-holiday-centers"] = None
>>> props["fixed-shift-convention"] = modified_following
>>> props["float-pay-period"] = 6
>>> props["float-pay-period-duration"] = months
>>> props["float-pay-basis"] = basis_act_365
>>> props["float-pay-holiday-centers"] = None
>>> props["float-shift-convention"] = modified_following
>>> props["index-basis"] = basis_act_365
>>> props["index-holiday-centers"] = None
>>> props["index-shift-convention"] = modified_following
>>> observables = generate_swap_observables(
... start = date(2007, Jun, 29)
... , end = date(2017, Jun, 29)
... , attributes = props
... , roll_period = 1
... , roll_duration = years
... , tenor_period = 10
... , tenor_duration = years)
>>> for o in observables: print o
0, 0, USD, [2007-Jun-29, 2017-Jun-29],
1, 0, USD, [2008-Jun-30, 2018-Jun-29],
2, 0, USD, [2009-Jun-29, 2019-Jun-28],
3, 0, USD, [2010-Jun-29, 2020-Jun-29],
4, 0, USD, [2011-Jun-29, 2021-Jun-29],
5, 0, USD, [2012-Jun-29, 2022-Jun-29],
6, 0, USD, [2013-Jun-28, 2023-Jun-29],
7, 0, USD, [2014-Jun-30, 2024-Jun-28],
8, 0, USD, [2015-Jun-29, 2025-Jun-30],
9, 0, USD, [2016-Jun-29, 2026-Jun-29],
'''
from ppf.date_time import days
shift = ppf.date_time.shift
if reset_lag > 0:
raise RuntimeError ("index lag expected less or equal to zero")
day, flow_id, all_observables = 0, 0, []
while day < end:
roll_start = start + roll_duration(flow_id*roll_period)
roll_end = start + roll_duration((flow_id+1)*roll_period)
reset_id = 0
proj_roll = roll_start
proj_start = \
shift(
proj_roll
, reset_shift_method
, reset_holiday_centres
)
proj_end = \
shift(
proj_roll+tenor_duration(tenor_period)
, reset_shift_method, reset_holiday_centres
)
reset_date = \
shift(
proj_start+days(reset_lag)
, reset_shift_method, reset_holiday_centres
)
all_observables.append(
swap_rate(
attributes
, flow_id
, reset_id
, reset_date
, reset_currency
, proj_start
, proj_end
, fixing(False)
, spread) )
flow_id += 1; reset_id += 1; day = roll_end
return all_observables
