New features since 0.1.0:
- Added event study analysis: an event study is a statistical method
to assess the impact of a particular event on the value of equities
and it is now possible to perform this analysis through the API
alphalens.tears.create_event_study_tear_sheet. Check out the
relative NoteBook in the example folder.
- Added support for group neutral factor analysis (group_neutral
argument): this affects the return analysis that is now able to
compute returns statistics for each group independently and
aggregate them together assuming a portfolio where each group has
equal weight.
- utils.get_clean_factor_and_forward_returns has a new parameter
max_loss that controls how much data the function is allowed to drop
due to not having enough price data or due to binning errors
(pandas.qcut). This gives the users more control on what is
happening and also avoid the function to raise an exception if the
binning doesn't go well on some values.
- Greatly improved API documentation
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