Trading Calendars

What is a Trading Calendar? 什么是交易日历?

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.

交易日历表示单个市场交易所的时序信息。 时序信息由两部分组成:会话和打开/关闭。这由Zipline TradingCalendar类表示,并用作所有新的TradingCalendar的父类。

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.

会话表示一组连续的分钟集合,并且具有UTC午夜标签。需要注意的是,会话标签不应被视为特定的时间点,并且UTC的午夜时间仅用于方便。

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.

在纽约证券交易所平均一天,市场在上午9:30开市,并在下午4点关闭。 交易时段可以根据交易所,一年中的某一天等而变化。

Why Should You Care About Trading Calendars? 为什么你应该关心交易日历?

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.

假设您想在周二买入一些股票,然后在周六卖出。 如果您交易该股票的交易所周六未开放,那么实际上当时不可能交易该股票,您必须等到周六之后的其他天数。 由于您无法将交易置于现实之中,因此您的回测在周六进行交易也是不合理的。

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.

为了让您对策略进行回溯测试,您的数据包中会记录日期,并且您的TradingCalendar中的日期应该匹配; 如果日期不匹配,那么你会看到一些错误。 这适用于分钟级数据和每日数据。

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:

如果我们要为交易所构建自己的TradingCalendar,TradingCalendar类具有许多我们应该考虑的属性。 这些包括如下属性:

  • 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

还有其他几个。 如果您想通过TradingCalendar API查看所有可用的属性和方法,请查看API参考

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

现在我们来看看伦敦证券交易所日历 LSEExchangeCalendar,下面是一个例子:

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 <http://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 建立自定义交易日历

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.

现在我们将建立自己的自定义交易日历。 此日历将用于交易可在24/7交易日历上交易的资产。 这意味着它将在星期一,星期二,星期三,星期四,星期五,星期六和星期日开放,交易所将于上午12点开盘并于晚上11:59结束。 我们将使用的时区是UTC。

First we’ll start off by importing some modules that will be useful to us. 首先,我们将通过导入一些对我们有用的模块开始。

# 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 zipline.utils.calendars import (
  register_calendar,
  TradingCalendar
)
from zipline.utils.memoize import lazyval

And now we’ll actually build this calendar, which we’ll call TFSExchangeCalendar: 现在我们将构建这个日历,我们将其称为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.

 为了让您使用此日历运行算法,您需要有一个数据包,其中您的资产的日期贯穿了一周中的所有日子。 您可以阅读如何在编写新包的文档中创建自己的数据包,或使用csvdir包从CSV文件创建包。
 

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