is backwards-compatible with the previous format.
In USEquityLoader, use dailyreader's trading_calendar.
This is backwards compatible and will fall back to the NYSE calendar if
the reader doesn’t have a calendar specified.
Instead of having separate ExchangeCalendar and TradingSchedule objects, we
now just have TradingCalendar. The TradingCalendar keeps track of each
session (defined as a contiguous set of minutes between an open and a close).
It's also responsible for handling the grouping logic of any given minute
to its containing session, or the next/previous session if it's not a market
minute for the given calendar.
`AverageDollarVolume` used `nanmean`, which discards NaNs before
averaging, giving an ADV which is too high for any equities that have
any NaNs.
Changing the method to `nansum` divided by window length so that the
denominator is the same no matter whether there are NaNs or not.
- Refactored EventsLoader and BlazeEventsLoader to not require a
subclass per dataset. Instead, you now pass a map from columns to
event fields directly to the EventsLoader constructor.
- Removed a large number of Quantopian-specific datasets and associated
tests.
- Rewrote the core logic of EventsLoader and BlazeEventsLoader to share
index calculations across multiple requested columns.
- Fixed a bug where event fields were incorrectly forward-filled when
null values were present in an event.
ENH: fast stochastic oscillator added.
A fast stochastic oscillator has been added to the technical
factors. This is the simplest of the stochastic oscillators,
and can be used to build the others.
Tests have been added that compare against the values expected
from that of ta-lib STOCHF.
FastStochasticOscillator is marked as window_safe=True to allow taking
moving averages for smoothing.
This query is often only cutting out a couple of months or a week of
data. The cost of computing this lower bound does not outway the cost of
sending back too much data.
Adds `mask_time_between` to do more efficient comparisons between
pandas.DatetimeIndex and datetime.time objects.
This is used in the loader utils to more efficiently normalize datetimes
around the query time.
Scott Sanderson