This is to fix the issue where 'GOOG_L's metadata lists its symbol as 'GOOG'. To resolve this, the 'file_name' is used as the canonical symbol, if it is given.
np.allclose creates a vector of size 1 if passed a scalar, which showed
up as a bottleneck in algorithms with a large number of
order_target_percent calls.
In d01e718373, we made a change for
compatibility with a change introduced in pip 7.0.0. Then the pip
maintainers went and reverted the change in pip 7.0.2, thereby
breaking our requirements file for the second time in ten days. This
change reverts the prior change so that we are once again compatible
with the current version of pip.
Also, to make it easier for people to avoid pip compatibility issues,
we're now specifying pip>=7.0.3 in etc/requirements.txt.
Test sources are now defined by the sim_params period_start and period_end, rather than by the period_start and a defined 'count' of bars. This allows us to consider the sim_params.period_end as the canonical definition of the end of a simulation.
Referencing context.account in handle_data() can block updates to account,
portfolio and performance metrics, which can cause unintended changes in
financial performance. Additionally, since context.account metrics are not
updating frequenctly enough (daily, rather than minutely) algos which base
decisions on these metrics can have undesired behavior.
To address this we do not base our decision to update performance on the
state of account_needs_update.
When we call get_account() from the market and minute close methods, we
set the performance_needs_update parameter to False since we just updated
performance.
_get_account() is renamed to _update_account() since the method does not
return account information.
Also remove redundant asset_needs_update = True lines.
Make the ordering in which processing of event types both explicit and
independent of the sort ordering of the incoming sources.
The overhead of creating the list per snapshot and the iterators appears
to be marginal in the minute data case when tested locally.
This patch is intended as part of the path towards making the trade
simulation loop not depend on consuming and tracking every trade event.
The timing of where last_sale_date was needed to be changed was proving
difficult to adapt in the previous model.
Should also allow the removal of sorting of the various source streams.
By having both the trade simulation main loop route events to "process"
methods based on event type and the process methods also checking event
type, there was some duplicated effort in doing that comparison many
times.
A particular case where this was noted in profiling was for the
`process_event` function which was checking if the type was not a trade
and returning early, when in a larger universe of stocks the value
returned False 99% of the time.
Instead provide separate process functions specific to each type,
e.g. e.g. `process_trade` and `process_transaction` and route traffic to
those functions in tradesimulation.
For a universe of 160 stocks on both no-op algo and an algo that rebuys
its universe every day, saw about a 10% increase locally.
Also:
- Add process_benchmark to blotter since internal subclass relies on
logic on benchmark, this allows the internal process_trade to be a
`pass`.
- Add warning on unrecoginzed event types.
The risk containers that are actually used for reports use the
'cumulative' style container which has an index of days, not minutes.
The minute containers and copying of data etc. were causing an expanding
memory footprint.
The intraday_risk_metrics is being removed since the values are not
used; cumulative risk metrics with the last value updated to the latest
close has been used for some time.
Before the removal of intraday_risk_metrics, the position trackers
passing of benchmark returns to the cumulative risk metrics needs to no
longer depend on the calculations done by the intraday stats. So instead
use the all_benchmark_returns stored in the tracker directly.
jfkirk