The only downstream contex that was using batch_order_target_percent
already had all necessary prices, so calling batch_order_target_percent
was wasteful.
This allows us to remove the check for whether the provided dt had a
time of midnight, which was a flimsy way to infer if the data frequency
was 'daily'. Besides the explicit check being preferable, this method
was broken on the futures calendar, since midnight is a valid market
minute.
Added as a subclass of MinuteEquityHistoryTestCase, where the primary
calendar is 'us_futures'.
Notes on modifications to MinuteEquityHistoryTestCase:
- To work on generic calendars, many tests now use set minutes for
window start and end, and check the values on active equity minutes.
- test_minute_regular should test against active equity minutes
- Adapts test_minute_midnight to work with futures calendar
- Use a method of getting the last open minute that works with
calendars that are open at midnight
- Test against Sunday at midnight, since the real intention of this
test is to check that given a non-open minute, we fall back to the
last open minute.
Added as a minimal subclass of DailyEquityHistoryTestCase, swapping out
just the primary calendar. This requires significant modifications to
DailyEquityHistoryTestCase, to allow for a generic primary calendar.
Previously, a dataframe passed into BcolzDailyBarWriter.write that was
missing an expected session between its first and last sessions would be
written incorrectly. Upon converting the dataframe to a ctable, the
values for all days following the gap would be shifted backwards, and
nans would be shifted in at the end.
This commit handles the issue by asserting that the number of rows in
the input table matches the number of sessions in the calendar between
the table's first and last sessions.
Also fixes a test that was mistakenly using minutes_in_range where it
should have been using sessions_in_range (uncovered by this change).
For futures, we need to divide the position’s commission by the
contract size to get a per-unit commission in order to properly update
the position’s cost basis.
Optimize session close lookups in MinuteResampleSessionBarReader:
- Adds `session_closes_in_range` method (along with
`session_opens_in_range`) to TradingCalendar to allow vectorized
retrieval of all values in a range of sessions.
- Improves code path for resampling a single session's worth of data (as
is the case when calling `get_value`), since we don't actually need to
look up the close minute.
When retrieving the open and close for a given session, we only care
about the scalar values, so using DataFrame.at instead of DataFrame.loc
is significantly faster.
Instead of recursively calling `DailyHistoryAggregator.closes` until we
find a non-nan close, we can instead call `load_raw_arrays` once, and
find the value from the returned array.
* ENH: Use regular rounding to calculate order amounts.
We previously tried to prevent accidental over-ordering by truncating
orders down unless they were within 1e-4 of the next higher integer.
Unfortunately, this makes it easy for a sell order to be one share short
of the desired position.
Using regular rounding treats both buys and sells in the same way.
* ENH keep non-rounding behavior consistent, but leave code structured to make easier to override
* DOC make round_order public and describe behavior in docstring
The CFE was closed along with the NYSE in observation of the days of
mourning in honor of the passing of presidents Gerald Ford and Ronald
Reagan. The CFE also observed the closures due to Hurricane Sandy,
along with NYSE. Adding those adhoc holidays to exchange_calendar_cfe
and removing them from cfe.csv in tests. To fit with
USNationalDaysofMourning, also removing the closure in observation of
the day of mourning in honor of the passing of president Nixon in
1994, despite the fact that the exchange did not exist at that time.
Signed-off-by: Maxwell Rounds <maxwell.j.rounds@gmail.com>
Richard Frank