使用 Pandas 创建交易假期日历

Question

我正在尝试使用 Pandas 创建一个交易日历。 我能够创建一个基于 USFederalHolidayCalendar 的 cal 实例。 USFederalHolidayCalendar 与交易日历不一致，因为交易日历不包括哥伦布日和退伍军人节。 但是，交易日历包括耶稣受难日（不包括在 USFederalHolidayCalendar 中）。 除了以下代码中的最后一行之外，所有内容都有效：

from pandas.tseries.holiday import get_calendar, HolidayCalendarFactory, GoodFriday
from datetime import datetime

cal = get_calendar('USFederalHolidayCalendar')  # Create calendar instance
cal.rules.pop(7)                                # Remove Veteran's Day rule
cal.rules.pop(6)                                # Remove Columbus Day rule
tradingCal = HolidayCalendarFactory('TradingCalendar', cal, GoodFriday)

TradingCal 实例似乎有效，因为我可以查看假期规则。

In[10]: tradingCal.rules
Out[10]: 
[Holiday: Labor Day (month=9, day=1, offset=<DateOffset: kwds={'weekday': MO(+1)}>),
 Holiday: Presidents Day (month=2, day=1, offset=<DateOffset: kwds={'weekday': MO(+3)}>),
 Holiday: Good Friday (month=1, day=1, offset=[<Easter>, <-2 * Days>]),
 Holiday: Dr. Martin Luther King Jr. (month=1, day=1, offset=<DateOffset: kwds={'weekday': MO(+3)}>),
 Holiday: New Years Day (month=1, day=1, observance=<function nearest_workday at 0x000000000A190BA8>),
 Holiday: Thanksgiving (month=11, day=1, offset=<DateOffset: kwds={'weekday': TH(+4)}>),
 Holiday: July 4th (month=7, day=4, observance=<function nearest_workday at 0x000000000A190BA8>),
 Holiday: Christmas (month=12, day=25, observance=<function nearest_workday at 0x000000000A190BA8>),
 Holiday: MemorialDay (month=5, day=31, offset=<DateOffset: kwds={'weekday': MO(-1)}>)]

当我尝试在日期范围内列出假期时，出现以下错误：

In[11]: tradingCal.holidays(datetime(2014, 12, 31), datetime(2016, 12, 31))
Traceback (most recent call last):
  File "C:\Python27\lib\site-packages\IPython\core\interactiveshell.py", line 3035, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-12-2708cd2db7a0>", line 1, in <module>
    tradingCal.holidays(datetime(2014, 12, 31), datetime(2016, 12, 31))
TypeError: unbound method holidays() must be called with TradingCalendar instance as first argument (got datetime instance instead)

有任何想法吗？

Answer 1

也许从头开始创建交易日历更直接，如下所示：

import datetime as dt

from pandas.tseries.holiday import AbstractHolidayCalendar, Holiday, nearest_workday, \
    USMartinLutherKingJr, USPresidentsDay, GoodFriday, USMemorialDay, \
    USLaborDay, USThanksgivingDay


class USTradingCalendar(AbstractHolidayCalendar):
    rules = [
        Holiday('NewYearsDay', month=1, day=1, observance=nearest_workday),
        USMartinLutherKingJr,
        USPresidentsDay,
        GoodFriday,
        USMemorialDay,
        Holiday('USIndependenceDay', month=7, day=4, observance=nearest_workday),
        USLaborDay,
        USThanksgivingDay,
        Holiday('Christmas', month=12, day=25, observance=nearest_workday)
    ]


def get_trading_close_holidays(year):
    inst = USTradingCalendar()

    return inst.holidays(dt.datetime(year-1, 12, 31), dt.datetime(year, 12, 31))


if __name__ == '__main__':
    print(get_trading_close_holidays(2016))
    #    DatetimeIndex(['2016-01-01', '2016-01-18', '2016-02-15', '2016-03-25',
    #                   '2016-05-30', '2016-07-04', '2016-09-05', '2016-11-24',
    #                   '2016-12-26'],
    #                  dtype='datetime64[ns]', freq=None)

Answer 2

如果有帮助，我对交易所交易日历也有类似的需求。 Quantopian 的 Zipline 项目中隐藏了一些优秀的代码。 我提取了相关部分并创建了一个新项目，用于在熊猫中创建市场交易所交易日历。 链接在这里，其中的一些功能如下所述。

https://github.com/rsheftel/pandas_market_calendars

https://pypi.python.org/pypi/pandas-market-calendars

以下是它可以通过创建纽约证券交易所所有有效开放时间的 pandas DatetimeIndex 来执行的操作：

import pandas_market_calendars as mcal
nyse = mcal.get_calendar('NYSE')

early = nyse.schedule(start_date='2012-07-01', end_date='2012-07-10')
early

                  market_open             market_close
=========== ========================= =========================
2012-07-02 2012-07-02 13:30:00+00:00 2012-07-02 20:00:00+00:00
2012-07-03 2012-07-03 13:30:00+00:00 2012-07-03 17:00:00+00:00
2012-07-05 2012-07-05 13:30:00+00:00 2012-07-05 20:00:00+00:00
2012-07-06 2012-07-06 13:30:00+00:00 2012-07-06 20:00:00+00:00
2012-07-09 2012-07-09 13:30:00+00:00 2012-07-09 20:00:00+00:00
2012-07-10 2012-07-10 13:30:00+00:00 2012-07-10 20:00:00+00:00

mcal.date_range(early, frequency='1D')

DatetimeIndex(['2012-07-02 20:00:00+00:00', '2012-07-03 17:00:00+00:00',
               '2012-07-05 20:00:00+00:00', '2012-07-06 20:00:00+00:00',
               '2012-07-09 20:00:00+00:00', '2012-07-10 20:00:00+00:00'],
               dtype='datetime64[ns, UTC]', freq=None)

mcal.date_range(early, frequency='1H')

DatetimeIndex(['2012-07-02 14:30:00+00:00', '2012-07-02 15:30:00+00:00',
               '2012-07-02 16:30:00+00:00', '2012-07-02 17:30:00+00:00',
               '2012-07-02 18:30:00+00:00', '2012-07-02 19:30:00+00:00',
               '2012-07-02 20:00:00+00:00', '2012-07-03 14:30:00+00:00',
               '2012-07-03 15:30:00+00:00', '2012-07-03 16:30:00+00:00',
               '2012-07-03 17:00:00+00:00', '2012-07-05 14:30:00+00:00',
               '2012-07-05 15:30:00+00:00', '2012-07-05 16:30:00+00:00',
               '2012-07-05 17:30:00+00:00', '2012-07-05 18:30:00+00:00',
               '2012-07-05 19:30:00+00:00', '2012-07-05 20:00:00+00:00',
               '2012-07-06 14:30:00+00:00', '2012-07-06 15:30:00+00:00',
               '2012-07-06 16:30:00+00:00', '2012-07-06 17:30:00+00:00',
               '2012-07-06 18:30:00+00:00', '2012-07-06 19:30:00+00:00',
               '2012-07-06 20:00:00+00:00', '2012-07-09 14:30:00+00:00',
               '2012-07-09 15:30:00+00:00', '2012-07-09 16:30:00+00:00',
               '2012-07-09 17:30:00+00:00', '2012-07-09 18:30:00+00:00',
               '2012-07-09 19:30:00+00:00', '2012-07-09 20:00:00+00:00',
               '2012-07-10 14:30:00+00:00', '2012-07-10 15:30:00+00:00',
               '2012-07-10 16:30:00+00:00', '2012-07-10 17:30:00+00:00',
               '2012-07-10 18:30:00+00:00', '2012-07-10 19:30:00+00:00',
               '2012-07-10 20:00:00+00:00'],
              dtype='datetime64[ns, UTC]', freq=None)

如果您只想获取可以在其他以该参数为参数的 Pandas 函数中使用的 Pandas Holiday Calendar：

holidays = nyse.holidays()

holidays.holidays[-5:]
(numpy.datetime64('2030-05-27'),
 numpy.datetime64('2030-07-04'),
 numpy.datetime64('2030-09-02'),
 numpy.datetime64('2030-11-28'),
 numpy.datetime64('2030-12-25'))

Answer 3

您必须创建类的新实例： cal1 = tradingCal() 。 这对我有用。

from pandas.tseries.holiday import get_calendar, HolidayCalendarFactory, GoodFriday
from datetime import datetime

cal = get_calendar('USFederalHolidayCalendar')  # Create calendar instance
cal.rules.pop(7)                                # Remove Veteran's Day rule
cal.rules.pop(6)                                # Remove Columbus Day rule
tradingCal = HolidayCalendarFactory('TradingCalendar', cal, GoodFriday)
print tradingCal.rules

#new instance of class
cal1 = tradingCal()

print cal1.holidays(datetime(2014, 12, 31), datetime(2016, 12, 31))

#DatetimeIndex(['2015-01-01', '2015-01-19', '2015-02-16', '2015-04-03',
#               '2015-05-25', '2015-07-03', '2015-09-07', '2015-11-26',
#               '2015-12-25', '2016-01-01', '2016-01-18', '2016-02-15',
#              '2016-03-25', '2016-05-30', '2016-07-04', '2016-09-05',
#               '2016-11-24', '2016-12-26'],
#              dtype='datetime64[ns]', freq=None, tz=None)

Answer 4

我使用相同的包采取了略有不同的方法：

https://pandas-market-calendars.readthedocs.io/en/latest/usage.html#exchange-open-valid-business-days

import calendar
from datetime import timedelta
import pandas_market_calendars as mcal

nyse = mcal.get_calendar('NYSE')
days = nyse.valid_days(start_date=today, end_date=today + timedelta(days=60))
if dt in days:
    print('ok')

因此，只需获取您的清单，检查您的交易日期是否合适，然后继续。