PerformanceReport

class PerformanceReport(report_id=None, name=None, position_source_id=None, position_source_type=None, parameters=None, earliest_start_date=None, latest_end_date=None, latest_execution_time=None, status=ReportStatus.new, percentage_complete=None, **kwargs)

Historical analyses on measures like PnL and exposure of a position source over a date range

Methods

__init__(report_id=None, name=None, position_source_id=None, position_source_type=None, parameters=None, earliest_start_date=None, latest_end_date=None, latest_execution_time=None, status=ReportStatus.new, percentage_complete=None, **kwargs)

Historical analyses on measures like PnL and exposure of a portfolio over a date range

Parameters:

• report_id (Optional[str]) – Marquee report ID

• name (Optional[str]) – report name

• position_source_id (Optional[str]) – position source ID

• position_source_type (Union[str, PositionSourceType, None]) – position source (i.e. ‘Portfolio’, ‘Asset’, or ‘Hedge’)

• parameters (Optional[ReportParameters]) – parameters of the report

• earliest_start_date (Optional[date]) – start date of report

• latest_end_date (Optional[date]) – end date of report

• latest_execution_time (Optional[datetime]) – date of the latest execution

• status (Union[str, ReportStatus]) – status of of report (i.e. ‘ready’, ‘executing’, or ‘done’)

• percentage_complete (Optional[float]) – percent of the report that is complete

Examples

>>> performance_report = PerformanceReport(
>>>     position_source_type=PositionSourceType.Portfolio,
>>>     position_source_id='PORTFOLIOID'
>>> )

delete()

Delete a report from Marquee

classmethod from_target(report)

classmethod get(report_id, **kwargs)

Get a performance report from the unique report identifier

Parameters:

report_id (str) – Marquee report ID

Returns:

returns a PerformanceReport object that correlates to the Marquee report

get_asset_count(start_date=None, end_date=None)

Get historical portfolio asset count

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_asset_count_long(start_date=None, end_date=None)

Get historical portfolio long asset count

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_asset_count_priced(start_date=None, end_date=None)

Get historical portfolio asset count priced

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_asset_count_short(start_date=None, end_date=None)

Get historical portfolio short asset count

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

Union[MDAPIDataBatchResponse, DataQueryResponse, tuple, list]

Returns:

returns a Pandas DataFrame with the results

get_aum(start_date, end_date)

Get AUM data for performance report

Parameters:

• start_date (date) – start date

• end_date (date) – end date

Returns:

dictionary of dates with corresponding AUM values

get_aum_source()

Get AUM Source for the portfolio associated with the performance report

Return type:

RiskAumSource

Returns:

aum source

get_brinson_attribution(benchmark=None, currency=None, include_interaction=False, aggregation_type=AttributionAggregationType.Arithmetic, start_date=None, end_date=None, return_format=ReturnFormat.DATA_FRAME)

Get PnL analytics called Brinson Attribution

Parameters:

• benchmark (Optional[str]) – benchmark’s unique Marquee identifier

• currency (Optional[Currency]) – currency of results; if none passed results default to your portfolio’s currency

• include_interaction (bool) – show interaction independent of security selection

• aggregation_type (AttributionAggregationType) – either artihmetic or geometric

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

• return_format (ReturnFormat) – return format; defaults to a Pandas DataFrame, but can be manually

set to ReturnFormat.JSON :rtype: Union[Dict, DataFrame] :return: Portfolio Brinson Attribution data for the requested date range

Examples

>>> brinson_attribution_results = performance_report.get_brinson_attribution (
>>>     benchmark=asset.get_marquee_id(),
>>>     include_interaction=True,
>>>     start_date=performance_report.earliest_start_date,
>>>     end_date=performance_report.latest_end_date,
>>> )
>>> display(pd.DataFrame(brinson_attribution_results))

get_custom_aum(start_date=None, end_date=None)

Get AUM data for performance report

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

List[CustomAUMDataPoint]

Returns:

list of AUM data between the specified range

get_gross_exposure(start_date=None, end_date=None)

Get historical portfolio gross exposure

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_long_exposure(start_date=None, end_date=None)

Get historical portfolio long exposure

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_many_measures(measures=None, start_date=None, end_date=None, return_format=ReturnFormat.DATA_FRAME)

Get many historical portfolio metrics

Parameters:

• measures (Optional[Tuple[str, ...]]) – a list of metrics

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

Union[Dict, DataFrame]

Returns:

returns a Pandas DataFrame with the results

get_measure(field, start_date=None, end_date=None, return_format=ReturnFormat.DATA_FRAME)

Get historical portfolio metrics

Parameters:

• field (str) – the entity property to be returned

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

Union[Dict, DataFrame]

Returns:

returns a Pandas DataFrame with the results

get_most_recent_job()

Retrieve the most current report job

get_net_exposure(start_date=None, end_date=None)

Get historical portfolio net exposure

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_pnl(start_date=None, end_date=None)

Get historical portfolio PnL

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_pnl_contribution(start_date=None, end_date=None, currency=None)

Get PnL Contribution broken down by constituents

Parameters:

• start_date (Optional[date]) – optional start date

• end_date (Optional[date]) – optional end date

• currency (Optional[Currency]) – optional currency; defaults to your portfolio’s currency

Return type:

DataFrame

Returns:

a Pandas DataFrame of results

get_portfolio_constituents(fields=None, start_date=None, end_date=None, return_format=ReturnFormat.DATA_FRAME)

Get historical portfolio constituents

Parameters:

• fields (Optional[List[str]]) – list of fields to include in the results

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

• return_format (ReturnFormat) – return format; defaults to a Pandas DataFrame, but can be manually

set to ReturnFormat.JSON :rtype: Union[Dict, DataFrame] :return: Portfolio constituent data for each day in the requested date range

get_positions_data(start=None, end=datetime.date(2023, 8, 14), fields=None, include_all_business_days=False)

get_servicing_cost_long_pnl(start_date=None, end_date=None)

Get historical portfolio servicing cost long PnL

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_servicing_cost_short_pnl(start_date=None, end_date=None)

Get historical portfolio servicing cost short PnL

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_short_exposure(start_date=None, end_date=None)

Get historical portfolio short exposure

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_trading_cost_pnl(start_date=None, end_date=None)

Get historical portfolio trading cost PnL

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_trading_pnl(start_date=None, end_date=None)

Get historical portfolio trading PnL

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

get_turnover(start_date=None, end_date=None)

Get historical portfolio turnover

Parameters:

• start_date (Optional[date]) – start date

• end_date (Optional[date]) – end date

Return type:

DataFrame

Returns:

returns a Pandas DataFrame with the results

run(start_date=None, end_date=None, backcast=False, is_async=True)

Run a report with the given date range

Parameters:

• start_date (Optional[date]) – start date (optional)

• end_date (Optional[date]) – end date (optional)

• backcast (bool) – set to true if the report should be backcasted; defaults to false

• is_async (bool) – return immediately (true) or wait for results (false); defaults to true

save()

Create a report in Marquee if it doesn’t exist. Update the report if it does.

schedule(start_date=None, end_date=None, backcast=None)

Schedule a report with the given date range

Parameters:

• start_date (Optional[date]) – start date (optional)

• end_date (Optional[date]) – end date (optional)

• backcast (Optional[bool]) – set to true if the report should be backcasted

set_aum_source(aum_source)

Set AUM Source for the portfolio associated with the performance report

Parameters:

aum_source (RiskAumSource) – aum source for portfolio

Returns:

aum source

set_position_source(entity_id)

Set position source type and position source ID

upload_custom_aum(aum_data, clear_existing_data=None)

Add AUM data for portfolio corresponding to the performance report

Parameters:

• aum_data (List[CustomAUMDataPoint]) – list of AUM data to upload

• clear_existing_data (Optional[bool]) – delete all previously uploaded AUM data for the portfolio (defaults to false)