Also, fix double emission of performance results with the last minute.
Change the perf tracker unit tests so that it doesn't rely on an
'extra' event triggering emission.
Unlike daily, minute emission now emits at the end of the bar in
the PerformanceTracker.transform instead of waiting for the next event.
During minute emissions, it is still helpful to have a final daily
performance result, analogous to what would be the final packet in
a daily emitted backtest, so that all transactions, etc. are contained
in one place.
Prevent an extra performance result with the timestamp of the midnight of
the day from being emitted.
Fix by setting the `saved_dt` value with the dt of the first event,
before entering into the main performance loop, otherwise a performance
result with a midnight timestamp and data from just the first event is
emitted.
The start and end of the simulation parameters should be 'normalized'
i.e. midnight timestamped.
However, the algorithm tests were using the timestamp of the
first and last trade, which were in market times,
i.e. 9:30 AM and 4:00 PM EST.
Fix passing the sim_params that is used to create the trade_history,
instead of having the sim_params inferred from the source.
(Also may want to consider fixing the logic that infers the date
range from the sources provided.)
Also, add a `num_days` option to `factory.create_simulation_parameters`
so that the a date range that covers the desired number of days is covered.
Since the default sim_params were covering a year, while the test only
supplies 4 values, causing an alignment issue with the record test,
since a years worth of results were returned, but there were only 4 events.
The cost value should always be a float.
The per share calculation shouldn't be changed dramatically by being
a float, (except for potential rounding errors), but change to so
that PerShare and PerTrade are aligned.
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When the cost basis was set to an integer the division in the
calculation would floor down to the nearest integer.
Ensuring that the number is a float during PerTrade's init
will ensure that the calculation doesn't use integer division.
Do the conversion to float in init rather than calculate, so that
calling the builtin `float` is not added to any inner loops.
As currently implemented, progress doesn't currently make sense with
minutely results. Dropping the field from the results so should help
reduce some noise.
Set the default end date to current date, so that trading on
'fresh' data is the default case.
Set the default begin date at 1/1/1990, since that is when the
treasury benchmark data is first available.
The intraday performance results were emitting all transactions
for the entire day up to that point, instead of the desired transaction
list for the current timestamp.
Add a `dt` parameter to the `to_dict` method of PerformancePeriod so
that the transactions are limited to a specific datetime.
When the parameter is `None`, a todays_performance object will
function as previously with returning all transactions for the day.
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The batch_transform decorator wipes out the doc string of the function
it wraps. Decorate the creator with functools.wraps to preserve function
metadata.
The indexing into performance results during the simulation loop fails
when emitting minutely since 'daily_perf' only exists on daily performance
results, not the minutely results.
Fix by making the key used to index into performance results depend
on the emission rate.
So that calculations that leverage the range of the treasury_curves,
like `pd.Series.searchsorted` will not overshoot the 'end' of the
range we are calculating risk metrics.
The treasury_duration member in RiskMetrics is never used except
for in unit tests.
Remove the saving of treasury_duration in preparation for the
move of the choose_treasury method out of the RiskMetrics classes.
Down the line, if we do restore the sanving of treasury_duration,
choose_treasury can return a tuple that includes treasury_duration
instead of just returning the rate.
To make the risk metrics being calculated more clear, change the
naming convention that ratios have a '_risk' suffix.
Also, fixes typo in beta docstring.
On ranges with missing data from Yahoo, e.g.:
On 2013-04-2 the date range of April 2013-03-29 failed because
of the first day in the range being Good Friday, and the API not
yet updating for the Monday after.
Handle the 404 that is found by raising and warning that no
benchmark data was found, but continuing on.
In the test factory creation of returns, the date creation was using
a timedelta of one day instead of incrementing by trading days.
Working towards changing risk module behavior which would leverage
the trading day map, but tests fail because non-trading days are
created.
Remove `factory.create_returns`, moving uses of that function to us
`factory.create_returns_from_period`, since the number of days input
for `create_returns` was more difficult to use when specifying ranges
over arbirtray dates.
Move the risk metric definitions to functions at the module level
with defined parameters.
Both risk implementations call these functions, where the difference
between risk implementations is with which internal data they
send to the various risk metrics.
Metrics moved:
- Sharpe Ratio
- Sortino Ratio
- Information Ration
- Alpha
Following the lead of the RiskMetricsBatch conversion to use
more pandas and numpy.
Bringing the iterative and batch versions closer together as we
work towards folding them into one.
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.
So that a filter function can filter out sids on a 'static' source,
when the universe of sids changes.
e.g. when using fetch_csv with a changing universe of stocks.
So that Transaction object behavior is exercised, uses the Transaction
object in performance module tests instead of ndict.
Also, adds fields to the __init__ of Transaction, to make the
definition of the object more well defined.
This function is unused, and on the general path of moving testing
functions out of gens.utils
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Slight refactoring of grouping the tracking variables in the
PerformanceTracker together.
So that it's easier to see which are config members and which are
members used to track internal state.
Eddie Hebert