The previous implementation had some issues and introduced undue
complexity. This implementation follows established patterns of
having the algorithm manager apply changes to the algorithm that
result from universe selection.
LastFillTime is updated on each partial/fill order event
LastUpdateTime is updated on each submitted order event w/ update count > 0
CancelTime is updated on canceled order events
Also fixes bug in regression algorithm where it used Time instead of UtcTime
for creating the SubmitOrderRequest object.
- removed IAlgorithm dependency from time in force handlers
- renamed GoodTilCancelled to GoodTilCanceled
- added GTC time in force in regression algorithms
- inlined initialization of time in force handler dictionary
- Use `MaximumDrawdownPercentPerSecurity` as `RiskManagementModel`.
- Modifies regression test to reflect risk model choice
- Use SetXXX to set models in python version
The fine enumerator factor accepts a 'date'. This date is that day
that the data is produced, so the emit time on that data is midnight
the following day. When we go to read the fine data we can't use the
current time because that's the 'emit time' -- instead we need to back
the time up a full day to find the correct start time. In addition,
the fine data was being read using UTC time stamps which led to even
more confusion here -- this change resolves both issues.
In addition to the above, the security.Fundamentals property wasn't being
properly set for the first time step when a security is selected due to
a bug in the subscription synchronizer not clearing out the universeData
in preparation for another loop (in the event changes != None).
The PairsTradingAlphaModel is a simple example of defining an insight
grouping. Insights that are grouped together are assigned a unique
group-id that can be used by the portfolio construction model.
Updates were made to the CommonAlphaModelTests to give more control to
derived types. Some changes are still needed here to give securities
unique prices. I would recommend using a psuedo-random walk approach
by using Random with a constant seed value.
Launcher project is packed as `QuantConnect.Lean`but as a mean ot having all Lean features just calling one package.
In the same sense, `QuantConnect.Algorithm.CSharp` is included as package and added as dependecy in the `QuantConnect.Lean` package just to have a working example aailable out-of-the-box.
The ScheduledUniverseSelectionModel wraps the new ScheduledUniverse.
ScheduledUniverse is similar to the UserDefinedUniverse we use to create
universes for dopbox/remote files w/ symbol listing. The new abstraction
that 'turns on' this no-data/scheduled based universe behavior is the
ITimeTriggeredUniverse, which exposes GetTriggerTimes which yields the
date/times your univese selection function will be called.
A regression algorithm was also added to cover the new feature.
VWAP will submit market orders while the current price is more favorable than VWAP.
STD will submit market orders while the current price is a configured number of
standard deviations away from the mean in the favorable direction.
Finalizes implementation of alpha framework, including alpha.spanner updates, many name changes, and harmonizes insight serialization with alpha streams API
Michael