Instead of calling a function, where the only parameter is the tracker
object, make it a method, so that the snapshot of position tracker stats
can be more easily called as `pt.stats()`.
The test had a check for a pandas version (0.12.0) which was out of date
with the version in requirements, meaning the tests have not been run
regularly and unstable.
Skip via the decorator to make it more noticeable that tests are not
being run.
Refer to cumulative and todays performance explicitly instead of always
looping through.
The third value (minute) for which this was useful, has been removed.
Also, there are some actions where only cumulative may need application,
e.g. application of dividends. (However, this patch does not remove
dividend processing from todays performance, but opens up later patches
to make that distinction.)
EarningsCalendar loader.
- Moves most of AdjustedArray back into Python. The window iterator is
the only part that's performance-intensive.
- Adds a bootleg templating system for creating specialized versions of
AdjustedArrayWindow for each concrete type we care about.
- Adds support for differently dtyped terms in pipeline. This allows us
to use datetime64s which are needed in the EarningsCalendar.
- Adds EarningsCalendar dataset for the next and previous earnings
announcements in pipeline.
- Adds in memory loader for EarningsCalendar.
- Adds blaze loader for EarningsCalendar.
Return -1 when there is a zero value for a spot price.
Intended for use by the incoming data portal changes. When the data
portal will see a -1 value, the portal will seek back a trading day
until a non-negative value is returned.
Volumes were incorrectly having the thousands factor applied, however
the volume is written as is (without the factor, since it volume is an
int, not float value.)
Fix by adding a special case for volume which returns the price as is.
Adds tests asserting that we resolve conflicts in accordance with the
following rules when we have multiple assets holding the same symbol at
the same time:
If multiple SIDs exist for symbol S at time T, return the candidate
SID whose start_date is highest. (200 cases)
If multiple SIDs exist for symbol S at time T, the best candidate
SIDs share the highest start_date, return the SID with the highest
end_date. (34 cases)
It is the opinion of the author (ssanderson) that we should consider
this malformed input and fail here. But this is the current indended
behavior of the code, and I accidentally broke it while refactoring.
These will serve as regression tests until the time comes that we
decide to enforce this as an error.
See https://github.com/quantopian/zipline/issues/837 for more
details.
Fixes the case where a delta has an asof_date of the last requested
day and an index error would occur. This guards against this
specifically to make the delta be effective through the end of the
requested window.
Adds a test case for this behavior.
Scott Sanderson