So that the 1-Month Sharpe ratio has a curve to use during calculation,
use data from 2002, since the Treasury returns 1 Month data starting
in July, 2001.
Highlights
- Reworked risk metrics, including verification against Excel spreadsheet
- Additional order methods
- Conversion of many data structures to use pandas
- Change to behavior of stop and limit orders (@pcawthron)
- Use pandas timezone handling throughout instead of Delorean
- New commission model (@stanh)
- Adds beginning of support for Toronto stock exchange. (@dstephens)
- Python 3 compatibility.
Unit tests now pass when run with Python 3.3, and Python 3 should
now be considered officially supported.
If anything does not work under Python 3, please file as a bug.
Python 2 and 3 throw different exception types when a file does
not exist.
Catch both exception types to trigger the download, so that the
loader works under both Python versions.
The compatibility between the two versions was made easier by
letting pandas handle the heavy lifting, so pass filenames to the
pandas serialization methods, instead of dealing doing the file
handling and reading/writing within the data module.
Use six's with_metaclass to have objects that use metaclasses, in
both Python 2 and 3.
Otherwise, in Python 3 the objects were being treated as if they
did not have a metaclass, when the Python 2 syntax is used, leading
to errors because of missing attributes, etc.
Use date sorted sources instead, instead of sorting with second
argument of Event, etc. since the `heapq.merge` behavior is using
the second part of the tuple, thus requiring a richer set of comparison
methods, which would only be used in the test context.
Use `date_sorted_sources` instead, so that sorting is done on algo time
and source id.
Python 3 removes the `.message` attribute, so use `str` instead.
Also, the divide by zero message has changed slightly between versions,
so just check for the exception type, instead of also checking the message.
The rename of walk is not provided by six, so check the import error
via an exception.
Also, callback behavior slightly changes between the two versions,
so instead iterate over the walked files and call what was formerly
a callback, directly as a function.
Python 3 uses the `__next__` method instead of `next`,
and uses the syntax of `next(foo)` accordingly.
Add `__next__` and `next` side-by-side so both Python 2 and 3 have
a method that can be used during iteration.
Instead of porting these cases of type checking, remove them instead.
Slightly more Python-ic to be more generous in what is allowed, and
the conversion to make these compatible with Python 3 are more trouble
than they are worth.
Python 3 requires submodules to have more explicit pathing, so use
the dot syntax to declare submodules which are in the same directory
as another module.
Use the six module to import functions and types that are
consistent between Python 2 and 3, so that one code base can
support both versions.
- Use integer types instead of int and long.
- Use string_types instead of basestring.
- Account for iteritems, itervalues, iterkeys.
- Use six.moves for filter and zip, reduce
- Use compatible bytes for md5 hasher.
- xrange and range
- Use `print()` function for all print calls
- Fix strip and format calls that were on the outside of the
print function for some reason.
(Which were breaking in Python 3 because of print returning None.)
- Remove commented out print calls.
Note that the calendar test is decorated with @nottest (as per the other calendar test functions). I've run the test to confirm the calendar works. The differences between the env (Yahoo Finance of GSPTSE) and the calendar are illustrated in the tradingcalendar_tse file and are confirmed to be errors on Yahoo Finance's part.
`for s in data` and methods like `for s in data.keys` were not producing
the same list of active sids
Make the other iteration methods match __iter__ by using the contains
method to check whether or not the sid is active.
For use of data outside of the algoscript context, which needs access
to all data fields use data._data
A bug in the create_random_simulation_parameters allows the period
start to be a non-trading day.
That bug was causing the commission tests to randomly fail, e.g.
when the period start was on Good Friday, because the commission was
created on hour three of Good Friday, instead of the next Monday.
When it hit that case, the test commission is never processed.
Defend against that bug by using the first open of the simulation
parameters which is more guaranteed to be during market hours,
when creating the test commission.
This is in place of fixing the bug in the random parameters function
or making the parameters non-random, which are other potential fixes.
So that each reference to `.portfolio` in the algoscript,
cache the value of the portfolio, and mark the need for a new
value at the end of each dt in the tradesimulation loop.
Eddie Hebert