PortfolioManager¶

class PortfolioManager(portfolio_id)[source]¶

Portfolio Manager is used to manage Marquee portfolios (setting entitlements, running and retrieving reports, etc)

Methods

__init__(portfolio_id)[source]¶

Initialize a Portfolio Manager

Parameters:: portfolio_id (str) – Portfolio ID

get_all_esg_data(measures=None, cards=None, pricing_date=None, benchmark_id=None)¶: Get all ESG Data :type measures: Optional[List[ESGMeasure]] :param measures: list of ESG Measures to include in results :type cards: Optional[List[ESGCard]] :param cards: list of ESG Cards to include in results :type pricing_date: Optional[date] :param pricing_date: optional pricing date; defaults to last previous business day :type benchmark_id: Optional[str] :param benchmark_id: optional benchmark asset ID to include in results :rtype: Dict :return: a dictionary of results

get_all_fund_of_fund_tags()[source]¶

If the portfolio is a fund of funds, this function will retrieve a list of dictionaries of all the tag sets associated with the sub-portfolios in the portfolio.

Return type:: List
Returns:: a list of tags as dictionaries

get_all_thematic_exposures(start_date=None, end_date=None, basket_ids=None, regions=None)¶

Deprecated since version 0.9.110: Please use the same function using the ThematicReport class

Return type:: DataFrame

get_aum(start_date, end_date)[source]¶

Get AUM data for portfolio

Parameters:

start_date (date) – start date
end_date (date) – end date

Returns:

dictionary of dates with corresponding AUM values

Deprecated since version 1.0.10: PortfolioManager.get_aum is now deprecated, please use PerformanceReport.get_aum instead.

get_aum_source()[source]¶

Get portfolio AUM Source

Return type:: RiskAumSource
Returns:: aum source

Deprecated since version 1.0.10: PortfolioManager.get_aum_source is now deprecated, please use PerformanceReport.get_aum_source instead.

get_bottom_five_thematic_exposures(start_date=None, end_date=None, basket_ids=None, regions=None)¶

Deprecated since version 0.9.110: Please use the same function using the ThematicReport class

Return type:: DataFrame

get_carbon_analytics(benchmark_id=None, reporting_year='Latest', currency=None, include_estimates=False, use_historical_data=False, normalize_emissions=False, cards=[<CarbonCard.COVERAGE: 'coverage'>, <CarbonCard.SBTI_AND_NET_ZERO_TARGETS: 'sbtiAndNetZeroTargets'>, <CarbonCard.EMISSIONS: 'emissions'>, <CarbonCard.ALLOCATIONS: 'allocations'>, <CarbonCard.ATTRIBUTION: 'attribution'>], analytics_view=CarbonAnalyticsView.LONG)¶

Return type:: Dict

get_carbon_attribution_table(benchmark_id, reporting_year='Latest', currency=None, include_estimates=False, use_historical_data=False, scope=CarbonScope.TOTAL_GHG, intensity_metric=CarbonEmissionsIntensityType.EI_ENTERPRISE_VALUE, analytics_view=CarbonAnalyticsView.LONG)¶

Return type:: DataFrame

get_carbon_coverage(reporting_year='Latest', include_estimates=False, use_historical_data=False, coverage_category=CarbonCoverageCategory.WEIGHTS, analytics_view=CarbonAnalyticsView.LONG)¶

Return type:: DataFrame

get_carbon_emissions(currency=None, include_estimates=False, use_historical_data=False, normalize_emissions=False, scope=CarbonScope.TOTAL_GHG, analytics_view=CarbonAnalyticsView.LONG)¶

Return type:: DataFrame

get_carbon_emissions_allocation(reporting_year='Latest', currency=None, include_estimates=False, use_historical_data=False, normalize_emissions=False, scope=CarbonScope.TOTAL_GHG, classification=CarbonEmissionsAllocationCategory.GICS_SECTOR, analytics_view=CarbonAnalyticsView.LONG)¶

Return type:: DataFrame

get_carbon_sbti_netzero_coverage(reporting_year='Latest', include_estimates=False, use_historical_data=False, target_coverage_category=CarbonTargetCoverageCategory.PORTFOLIO_EMISSIONS, analytics_view=CarbonAnalyticsView.LONG)¶

Return type:: DataFrame

get_custom_aum(start_date=None, end_date=None)[source]¶

Get AUM data for portfolio

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

Deprecated since version 1.0.10: PortfolioManager.get_custom_aum is now deprecated, please use PerformanceReport.get_custom_aum instead.

get_entitlements()¶

Return type:: Entitlements

get_esg_bottom_ten(measure, pricing_date=None)¶: Get entity constituents with the ten lowest ESG percentile values :type measure: ESGMeasure :param measure: ESG Measure :type pricing_date: Optional[date] :param pricing_date: optional pricing date; defaults to last previous business day :rtype: DataFrame :return: a Pandas DataFrame with results

get_esg_by_region(measure, pricing_date=None)¶: Get breakdown of entity by region, along with the weighted average score of the compositions in each region :type measure: ESGMeasure :param measure: ESG Measure :type pricing_date: Optional[date] :param pricing_date: optional pricing date; defaults to last previous business day :rtype: DataFrame :return: a Pandas DataFrame with results

get_esg_by_sector(measure, pricing_date=None)¶: Get breakdown of entity by sector, along with the weighted average score of the compositions in each sector :type measure: ESGMeasure :param measure: ESG Measure :type pricing_date: Optional[date] :param pricing_date: optional pricing date; defaults to last previous business day :rtype: DataFrame :return: a Pandas DataFrame with results

get_esg_quintiles(measure, pricing_date=None)¶: Get breakdown of entity by weight in each percentile quintile for requested ESG measure :type measure: ESGMeasure :param measure: ESG Measure :type pricing_date: Optional[date] :param pricing_date: optional pricing date; defaults to last previous business day :rtype: DataFrame :return: a Pandas DataFrame with results

get_esg_summary(pricing_date=None)¶

Return type:: DataFrame

get_esg_top_ten(measure, pricing_date=None)¶: Get entity constituents with the ten highest ESG percentile values :type measure: ESGMeasure :param measure: ESG Measure :type pricing_date: Optional[date] :param pricing_date: optional pricing date; defaults to last previous business day :return: a Pandas DataFrame with results

get_factor_risk_report(risk_model_id=None, fx_hedged=None, benchmark_id=None, tags=None)¶

Return type:: FactorRiskReport

get_factor_risk_reports(fx_hedged=None, tags=None)¶

Return type:: List[FactorRiskReport]

get_latest_position_set(position_type=PositionType.CLOSE)¶

Return type:: PositionSet

get_macro_exposure(model, date, factor_type, factor_categories=[], get_factors_by_name=True, tags=None, return_format=ReturnFormat.DATA_FRAME)[source]¶

Get portfolio and asset exposure to macro factors or macro factor categories

Parameters:

model (MacroRiskModel) – the macro risk model
date (date) – date for which to get exposure
factor_type (FactorType) – whether to get exposure to factor categories or factors.
factor_categories (List[Factor]) – Get portfolio exposure to these factor categories. Must be valid Factor Categories.

If factor_type is Factor, get exposure to factors that are grouped in these factor categories. If empty, return exposure to all factor categories/factors. :type get_factors_by_name: bool :param get_factors_by_name: whether to identify factors by their name or identifier :type tags: Optional[Dict] :param tags: If the portfolio is a fund of funds, pass in a dictionary corresponding to the tag values to retrieve results for a sub-portfolio :type return_format: ReturnFormat :param return_format: whether to return a dict or a pandas dataframe :rtype: Union[Dict, DataFrame] :return: a Pandas Dataframe or a Dict of portfolio exposure to macro factors

Examples

>>> model = MacroRiskModel.get("MODEL")
>>> pm = PortfolioManager("PORTFOLIO ID")
>>> exposure_dataframe = pm.get_macro_exposure(
>>>     model=model,
>>>     date=dt.date(2022, 1, 1),
>>>     factor_type=FactorType.Factor
>>> ).sort_values(
>>>     by=["Total Factor Exposure"],
>>>     axis=1,
>>>     ascending=False
>>> )

get_performance_report(tags=None)[source]¶

Get performance report associated with a portfolio

Parameters:: tags (Optional[Dict]) – If the portfolio is a fund of funds, pass in a dictionary corresponding to the tag values

to retrieve results for a sub-portfolio :rtype: PerformanceReport :return: returns the PerformanceReport associated with portfolio if one exists

get_pnl_contribution(start_date=None, end_date=None, currency=None, tags=None)[source]¶

Get PnL Contribution of your portfolio 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
tags (Optional[Dict]) – If the portfolio is a fund of funds, pass in a dictionary corresponding to the tag values

to retrieve results for a sub-portfolio :rtype: DataFrame :return: a Pandas DataFrame of results

Deprecated since version 0.9.110: Please use the get_pnl_contribution on your portfolio’s performance report usingthe PerformanceReport class

get_position_dates()¶

Return type:: Tuple[date, ...]

get_position_set_for_date(date, position_type=PositionType.CLOSE)¶

Return type:: PositionSet

get_position_sets(start=datetime.date(1952, 1, 1), end=datetime.date(2023, 8, 14), position_type=PositionType.CLOSE)¶

Return type:: List[PositionSet]

get_positions_data(start=datetime.date(1952, 1, 1), end=datetime.date(2023, 8, 14), fields=None, position_type=PositionType.CLOSE)¶

get_reports(tags=None)¶

Return type:: List[Report]

get_schedule_dates(backcast=False)[source]¶

Get recommended start and end dates for a portfolio report scheduling job

Parameters:: backcast (bool) – true if reports should be backcasted
Return type:: List[date]
Returns:: a list of two dates, the first is the suggested start date and the second is the suggested end date

get_status_of_reports(tags=None)¶

Return type:: DataFrame

get_tag_name_hierarchy()[source]¶

Get the list of tags by name by which a portfolio’s fund of funds are structured in that order

Return type:: List
Returns:: a list of tag names

get_thematic_beta(basket_identifier, start=datetime.date(1952, 1, 1), end=datetime.date(2023, 8, 14))¶

Return type:: DataFrame

get_thematic_breakdown(date, basket_id)¶: Get a by-asset breakdown of a portfolio or basket’s thematic exposure to a particular flagship basket on a particular date :type date: date :param date: date :type basket_id: str :param basket_id: GS flagship basket’s unique Marquee ID :rtype: DataFrame :return: a Pandas DataFrame with results

get_thematic_exposure(basket_identifier, notional=10000000, start=datetime.date(1952, 1, 1), end=datetime.date(2023, 8, 14))¶

Return type:: DataFrame

get_thematic_report(tags=None)¶

Return type:: ThematicReport

get_top_five_thematic_exposures(start_date=None, end_date=None, basket_ids=None, regions=None)¶

Deprecated since version 0.9.110: Please use the same function using the ThematicReport class

Return type:: DataFrame

poll_report(report_id, timeout=600, step=30)¶

Return type:: ReportStatus

run_reports(start_date=None, end_date=None, backcast=False, is_async=True, months_per_batch=None)[source]¶

Run all reports associated with a portfolio

Parameters:

start_date (Optional[date]) – start date of report job
end_date (Optional[date]) – end date of report job
backcast (bool) – true if reports should be backcasted; defaults to false
is_async (bool) – true if reports should run asynchronously; defaults to true
months_per_batch (Optional[int]) – batch size of historical report job schedules in number of months; defaults to false

if set, historical reports are scheduled in batches of size less than or equal to the given number of months :rtype: List[Union[DataFrame, ReportJobFuture]] :return: if is_async is true, returns a list of ReportJobFuture objects; if is_async is false, returns a list of dataframe objects containing report results for all portfolio results

Examples

>>> pm = PortfolioManager("PORTFOLIO ID")
>>> report_results = pm.run_reports(backcast=True)

for longer hisotry, use months_per_batch to schedule reports in batches of 6 months >>> pm = PortfolioManager(“PORTFOLIO ID”) >>> pm.schedule_reports(backcast=False, months_per_batch=6)

schedule_reports(start_date=None, end_date=None, backcast=False, months_per_batch=None)[source]¶

Schedule all reports associated with a portfolio. If months_per_batch is passed and reports are historical, then schedule them in batches of bathc_period months. Backcasted reported can’t be batched.

Parameters:

start_date (Optional[date]) – start date of report job (optional)
end_date (Optional[date]) – end date of report job (optional)
backcast (bool) – true if reports should be backcasted; defaults to false
months_per_batch (Optional[int]) – batch size of historical report job schedules in number of months; defaults to false

if set, historical reports are scheduled in batches of size less than or equal to the given number of months

Examples

>>> pm = PortfolioManager("PORTFOLIO ID")
>>> pm.schedule_reports(backcast=False)

for a portfolio having hisotry greater than 1 yr, use months_per_batch to schedule reports in batches of 6 months >>> pm = PortfolioManager(“PORTFOLIO ID”) >>> pm.schedule_reports(backcast=False, months_per_batch=6)

set_aum_source(aum_source)[source]¶

Set portfolio AUM Source

Parameters:: aum_source (RiskAumSource) – aum source for portfolio
Returns:: aum source

Deprecated since version 1.0.10: PortfolioManager.set_aum_source is now deprecated, please use PerformanceReport.set_aum_source instead.

set_currency(currency)[source]¶

Set the currency of a portfolio

Parameters:: currency (Currency) – Currency

set_entitlements(entitlements)[source]¶

Set the entitlements of a portfolio

Parameters:: entitlements (Entitlements) – Entitlements object

Examples

>>> portfolio_admin_emails = ['LIST OF ADMIN EMAILS']
>>> portfolio_viewer_emails = ['LIST OF VIEWER EMAILS']
>>> admin_entitlements = EntitlementBlock(users=User.get_many(emails=portfolio_admin_emails))
>>> view_entitlements = EntitlementBlock(users=User.get_many(emails=portfolio_viewer_emails))
>>>
>>> entitlements = Entitlements(
>>>    view=view_entitlements,
>>>    admin=admin_entitlements
>>> )
>>>
>>> pm = PortfolioManager("PORTFOLIO ID")
>>> pm.set_entitlements(entitlements)

set_tag_name_hierarchy(tag_names)[source]¶

Set the list of tags by name by which a portfolio’s fund of funds are structured in that order

Parameters:: tag_names (List) – a list of tag names in order of the new fund of funds structure

update_portfolio_tree()[source]¶: After a modification is made on your portfolio (reports are added/modified, the tag name hierarchy is changed, etc), run this function so those changes reflect across all the portfolio’s sub-portfolios

update_positions(position_sets, net_positions=True)¶

upload_custom_aum(aum_data, clear_existing_data=None)[source]¶

Add AUM data for portfolio

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)

Deprecated since version 1.0.10: PortfolioManager.upload_custom_aum is now deprecated, please use PerformanceReport.upload_custom_aum instead.