Trading Calendars¶

What is a Trading Calendar?¶

A trading calendar represents the timing information of a single market exchange. The timing information is made up of two parts: sessions, and opens/closes. This is represented by the Zipline TradingCalendar class, and is used as the parent class for all new TradingCalendar s.

A session represents a contiguous set of minutes, and has a label that is midnight UTC. It is important to note that a session label should not be considered a specific point in time, and that midnight UTC is just being used for convenience.

For an average day of the New York Stock Exchange, the market opens at 9:30AM and closes at 4PM. Trading sessions can change depending on the exchange, day of the year, etc.

Why Should You Care About Trading Calendars?¶

Let’s say you want to buy a share of some equity on Tuesday, and then sell it on Saturday. If the exchange in which you’re trading that equity is not open on Saturday, then in reality it would not be possible to trade that equity at that time, and you would have to wait until some other number of days past Saturday. Since you wouldn’t be able to place the trade in reality, it would also be unreasonable for your backtest to place a trade on Saturday.

In order for you to backtest your strategy, the dates in that are accounted for in your data bundle and the dates in your TradingCalendar should match up; if the dates don’t match up, then you you’re going to see some errors along the way. This holds for both minutely and daily data.

The TradingCalendar Class¶

The TradingCalendar class has many properties we should be thinking about if we were to build our own TradingCalendar for an exchange. These include properties such as:

Name of the Exchange

Timezone

Open Time

Close Time

Regular & Ad hoc Holidays

Special Opens & Closes

And several others. If you’d like to see all of the properties and methods available to you through the TradingCalendar API, please take a look at the API Reference

Now we’ll take a look at the London Stock Exchange Calendar LSEExchangeCalendar as an example below:

class LSEExchangeCalendar(TradingCalendar):
  """
  Exchange calendar for the London Stock Exchange

  Open Time: 8:00 AM, GMT
  Close Time: 4:30 PM, GMT

  Regularly-Observed Holidays:
    - New Years Day (observed on first business day on/after)
    - Good Friday
    - Easter Monday
    - Early May Bank Holiday (first Monday in May)
    - Spring Bank Holiday (last Monday in May)
    - Summer Bank Holiday (last Monday in May)
    - Christmas Day
    - Dec. 27th (if Christmas is on a weekend)
    - Boxing Day
    - Dec. 28th (if Boxing Day is on a weekend)
  """

  @property
  def name(self):
    return "LSE"

  @property
  def tz(self):
    return timezone('Europe/London')

  @property
  def open_time(self):
    return time(8, 1)

  @property
  def close_time(self):
    return time(16, 30)

  @property
  def regular_holidays(self):
    return HolidayCalendar([
      LSENewYearsDay,
      GoodFriday,
      EasterMonday,
      MayBank,
      SpringBank,
      SummerBank,
      Christmas,
      WeekendChristmas,
      BoxingDay,
      WeekendBoxingDay
    ])

You can create the Holiday objects mentioned in def regular_holidays(self)` through the `pandas <https://pandas.pydata.org/pandas-docs/stable/>`__ module, ``pandas.tseries.holiday.Holiday, and also take a look at the LSEExchangeCalendar code as an example, or take a look at the code snippet below.

from pandas.tseries.holiday import (
    Holiday,
    DateOffset,
    MO
)

SomeSpecialDay = Holiday(
    "Some Special Day",
    month=1,
    day=9,
    offset=DateOffSet(weekday=MO(-1))
)

Building a Custom Trading Calendar¶

Now we’ll build our own custom trading calendar. This calendar will be used for trading assets that can be traded on a 24/7 exchange calendar. This means that it will be open on Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, and Sunday, and the exchange will open at 12AM and close at 11:59PM. The timezone which we’ll use is UTC.

First we’ll start off by importing some modules that will be useful to us.

# for setting our open and close times
from datetime import time
# for setting our start and end sessions
import pandas as pd
# for setting which days of the week we trade on
from pandas.tseries.offsets import CustomBusinessDay
# for setting our timezone
from pytz import timezone

# for creating and registering our calendar
from trading_calendars import register_calendar, TradingCalendar
from zipline.utils.memoize import lazyval

And now we’ll actually build this calendar, which we’ll call TFSExchangeCalendar:

class TFSExchangeCalendar(TradingCalendar):
  """
  An exchange calendar for trading assets 24/7.

  Open Time: 12AM, UTC
  Close Time: 11:59PM, UTC
  """

  @property
  def name(self):
    """
    The name of the exchange, which Zipline will look for
    when we run our algorithm and pass TFS to
    the --trading-calendar CLI flag.
    """
    return "TFS"

  @property
  def tz(self):
    """
    The timezone in which we'll be running our algorithm.
    """
    return timezone("UTC")

  @property
  def open_time(self):
    """
    The time in which our exchange will open each day.
    """
    return time(0, 0)

  @property
  def close_time(self):
    """
    The time in which our exchange will close each day.
    """
    return time(23, 59)

  @lazyval
  def day(self):
    """
    The days on which our exchange will be open.
    """
    weekmask = "Mon Tue Wed Thu Fri Sat Sun"
    return CustomBusinessDay(
      weekmask=weekmask
    )

Conclusions¶

In order for you to run your algorithm with this calendar, you’ll need have a data bundle in which your assets have dates that run through all days of the week. You can read about how to make your own data bundle in the Writing a New Bundle documentation, or use the csvdir bundle for creating a bundle from CSV files.