The bar timestamps for day start and finish, for NYSE traded stocks,
should be 9:31 AM EST to 4:00 PM EST, for a total of 390 minutes.
Fix starting at 9:30 AM and the creation of 391 bars.
- Add transaction and order types
- Move TransactionSimulator from trading.py to tradesimulation.py
(only used by other members of the tradesimulation module)
- Make Transaction an independent event, like dividend
- Add Blotter class.
- Flatten the transaction events to be independent of trade bar events
- Make orders into events that reach performance (need to add
handling)
- Issue IDs to orders and tracking each transaction's order id.
- Make volume share slippage fill orders independently, rather than
aggregating them into a single transaction.
- Perf tracker holds orders, serializes them with transactions.
- Order state defined and maintained by order class.
- Minutely emission of orders based on last_modified date.
So that the environments' exchange time is used without having to
specify it independently.
Also, moves uses of Delorean.shift for the exchange conversion inside
of environment to use the exchange_dt_to_utc method.
Wires up performance tracker so that when `emission_rate` is set
to `minute`, the performance packets are sent out every minute,
instead of once per day.
Please note, the performance packets that are generated are not
ready for prime time consumption, this patch is merely a step towards
hooking up the ability to inspect minute data.
Known issues:
- The packets do not currently include risk information.
Since we need to consider how this affects the denominators
of the risk calculations.
- added LSE reference rrules calendar (thanks to Edward Johns)
- added tests to verify LSE environment matches rrule calendar
- added a test to verify global environment behavior can be set.
- moved DailyReturn class to trading to eliminate circularity from
risk <-> trading.
- updated TradingEnvironment to be a context manager. This allows users
to run algorithms in individually isolated environments in one python
process. This is useful for managing multiple algorithms in a single
ipython notebook.
- added comments to explain behavior and useage of the global environment
Global state for the financial simulation environment is accessed through the
zipline.finance.trading module, which now contains a module variable:
environment.
Parameters are passed into an algorithm as a keyword argument, sim_params.
SimulationParameters creates a trading day index for the test period that
can be used to find trading days, calculate distance between trading days,
and other common operations. The sim params index is just selected from the
global state.
================
Details:
- adding delorean to the requirements.
- made index symbol a parameter for loading the benchmark data. changed
messagepack storage to be symbol specific.
- ported risk, performance, algorithm, transforms, batch transforms
and associated tests to use simulation parameters and global environment
- factory and sim factory use global state and sim params
- factory method parameter names now reflect the class expected
Previously, the list was generated, but only used to calculate
the number of days in the environment.
With exposing this list, working towards a path where the simulation
uses the trading days to determine when to handle market closes.
Updated the search for treasury data when there is none for the
test end date.
It could be that the end date is not a trading day, or we could
just be missing treasury data. In either case, we try to recover
more gracefully now, by searching as far as possible and maybe
logging a warning.
Similarly, if there is no benchmark data for the test end date,
look for the next trading day. If we really have no data,
blow up with our own explicit exception, instead of overflowing
in our search for dates in the future.
Moved grouping by date earlier in the pipeline of generators,
prior to any date-dependent state getting involved. Grouping
pulls from the pipeline until the start of the next group,
which is in the next day. The effect of grouping after
slippage but before handle_data is that slippage and the algo
are out of sync by a transaction.
Mostly whitespace, line width and other spacing changes.
Also, removes use of deprecated has_key in favor of `in`
Going forward new patches should pass running `flake8` before
submission.
Eddie Hebert