FactSet Estimates

These functions provide data from the “FactSet Estimates - Consensus” data set, which provides KPI data with comparable actuals and consensus estimates, sourced from 800+ contributors. (See https://www.factset.com/marketplace/catalog/product/factset-estimates-consensus)

fs_actual(parameter, /, freq='FQ/FS', alignment='afp', *, currency=None, currency_method=None)

Retrieves time series with the Actuals values from the FactSet Estimates dataset.

Parameters:

• parameter (str) – A FactSet estimates data item.

• freq (str) – A fiscal frequency: FQ/FS, FQ, FS, FY or LTM.

• alignment – An alignment: afp, fp, pd or rd.

• currency (str) – Optionally, a three-letter currency code (e.g. USD or EUR). If a currency is given, the values are converted to the given currency.

• currency_method (str) – How the exchange rate is determined. Either 'mean' (use the average exchange rate over the fiscal period) or 'last' (use the exchange rate of the last day in the fiscal period). The default value is 'mean'. See interval-based currency conversion.

Examples:

Actual interim (quarterly / semi-annual) sales for a company:

fs_actual('sales')

Actual interim sales in USD:

fs_actual('sales', currency='USD')

Actual annual sales:

fs_actual('sales', freq='FY')

fs_consensus(parameter, /, statistic='mean', freq='FQ/FS', alignment='afp', unreported_periods=None, *, currency: str, currency_method: str, relative_to: str, relative_days: int)

Retrieves time series of consensus estimates for each period from the FactSet Estimates dataset. The latest consensus value for each fiscal period is returned by default; for historical periods this is the consensus before results were reported.

Parameters:

• parameter (str) – A FactSet estimates data item.

• statistic (str) – The type of the statistic to fetch. The options are 'mean', 'median', 'min', 'max', 'stdev' (standard deviation of broker estimates), 'count' (number of broker estimates), 'up' (number of broker estimates revised upwards) and 'down' (number of broker estimates revised downwards). The default value is 'mean'.

• freq (str) – A fiscal frequency: FQ/FS, FQ, FS or FY.

• alignment – An alignment: afp, fp, pd or rd.

• unreported_periods (int) – Number of unreported periods to return. The default is None, which returns all unreported periods.

• currency (str) – Optionally, a three-letter currency code (e.g. USD or EUR). If a currency is given, the values are converted to the given currency.

• currency_method (str) – How the exchange rate is determined. Either 'mean' (use the average exchange rate over the fiscal period) or 'last' (use the exchange rate of the last day in the fiscal period). The default value is 'mean'. See interval-based currency conversion.

• relative_to (str) – Optionally, the known time of the data for each fiscal period. Either 'afp' (the last date of the fiscal period) or 'pd' (publication date). If provided, the signal produces data as they were known at the given date relative to each fiscal period. The known time can be further modified by the relative_days argument. If not provided, the last available consensus estimate is returned.

• relative_days (int) – Optionally, the number of days the known time should be moved relative to the date defined by the relative_to argument. A negative value signifies an earlier known time, while a positive value signifies a later known time. For example, relative_to='afp', relative_days=2 means that the known time is two days after the last date of the fiscal period. This argument requires the argument relative_to to be set. The default value is 0. If relative_to is set to 'pd', the value cannot be positive.

Examples:

Consensus interim sales for a company:

fs_consensus('sales')

Number of brokers for consensus interim sales:

fs_consensus('sales', 'count')

Consensus interim sales, as of quarter-end for each fiscal period:

fs_consensus('sales', relative_to='afp')

Consensus interim sales, 30 days before quarter-end for each fiscal period:

fs_consensus('sales', relative_to='afp', relative_days=-30)

fs_metric(parameter, /, freq='FQ/FS', alignment='afp', statistic='mean', unreported_periods=None, *, currency, currency_method, relative_to, relative_days)

Retrieves the combination of actuals (for historical periods) and consensus estimates (for future periods) as a single time series. This is a convenience method, and can be used, for example, when you want to calculate the year-over-year change for some FactSet time series, and you want to compare next quarter’s consensus estimates with the corresponding quarter in last year’s actuals.

Parameters:

• parameter (str) – A FactSet estimates data item.

• freq (str) – A fiscal frequency: FQ/FS, FQ, FS or FY.

• alignment – An alignment: afp, fp, pd or rd.

• statistic (str) – The type of the statistic to fetch. The options are 'mean', 'median', 'min' and 'max'. The default value is 'mean'.

• unreported_periods (int) – Number of unreported periods to return. Default is None, which returns all unreported periods.

• currency (str) – Optionally, a three-letter currency code (e.g. USD or EUR). If a currency is given, the values are converted to the given currency.

• currency_method (str) – How the exchange rate is determined. Either 'mean' (use the average exchange rate over the fiscal period) or 'last' (use the exchange rate of the last day in the fiscal period). The default value is 'mean'. See interval-based currency conversion.

• relative_to (str) – Optionally, the known time of the data for each fiscal period. Either 'afp' (the last date of the fiscal period) or 'pd' (publication date). If provided, the signal produces data as they were known at the given date relative to each fiscal period. The known time can be further modified by the relative_days argument. If not provided, the last available consensus estimate is returned.

• relative_days (int) – Optionally, the number of days the known time should be moved relative to the date defined by the relative_to argument. A negative value signifies an earlier known time, while a positive value signifies a later known time. For example, relative_to='afp', relative_days=2 means that the known time is two days after the last date of the fiscal period. This argument requires the argument relative_to to be set. The default value is 0. If relative_to is set to 'pd', the value cannot be positive.

Example:

To calculate year-over-year change in interim sales, where historical periods are based on reported data, and future periods are based on consensus:

fs_metric('sales').relative_change(years=1)

fs_revisions(parameter, /, period, statistic='mean', *, calendarize: str, calendarize_from_freq: str)

Retrieve revisions of the consensus estimate for a given accounting period.

Parameters:

• parameter (str) – A FactSet estimates data item.

• period (str) – A single fiscal period or a rolling relative period.

• statistic (str) – The type of the statistic to fetch. The options are 'mean', 'median', 'min', 'max', 'stdev' (standard deviation of broker estimates), 'count' (number of broker estimates), 'up' (number of broker estimates revised upwards) and 'down' (number of broker estimates revised downwards). The default value is 'mean'.

• calendarize (str) – If period is a calendarized period, this specifies how the calendarization is performed. Either blended (default), last or nearest. See calendarization methods for details.

• calendarize_from_freq (str) – If period is a calendarized period, the frequency of the signal which the calendarization is based on. Either FQ/FS, FQ, FS or FY. If period specifies a calendar year, the default is FQ/FS, if it specifies a quarter, the default is FQ, and if it specifies a semi-annual period, the default is FS.

Examples:

Consensus sales revisions for fiscal 1Q-2024:

fs_revisions('sales', '1Q-2024')

Consensus sales revisions for the current fiscal year (FY1):

fs_revisions('sales', 'FY1')

Consensus sales revisions for the current fiscal year on a rolling basis (GY1):

fs_revisions('sales', 'GY1')

fs_revisions_change(parameter, /, period, statistic='mean', *, freq: str = 'D', days: int, weeks: int, months: int, years: int, relative: bool = True)

Calculate the change in the FactSet revisions for a rolling fiscal period.

For each date d in the output, the value is calculated in the following way:

1. Determine the correct fiscal period p relative to d. (If period is GY1, p is the fiscal year which contains d; if it is GY2 it is the next fiscal year, and so on.)

2. Determine the interval the change is to be calculated over. The interval ends on d and its length is determined by the arguments days/weeks/months/years.

3. Take the latest revision for p known at the start of the interval and the latest revision known at the end of the interval and calculate the change.

Exactly one of the arguments days, weeks, months and years must be specified.

Parameters:

• parameter (str) – A FactSet estimates data item.

• period (str) – A rolling fiscal period. The supported options are GYn, GQn, GSn and GQ/GSn.

• statistic (str) – The type of the statistic to fetch. The options are 'mean', 'median', 'min', 'max', 'stdev' (standard deviation of broker estimates), 'count' (number of broker estimates), 'up' (number of broker estimates revised upwards) and 'down' (number of broker estimates revised downwards).

• freq (str) – The frequency of the output. The output time series will have a data point on the last date of each period. The supported values are Y (annual), M (monthly), W (weekly, ending on Sunday), W-MON etc. (weekly, ending on the specified day) and D (daily).

• days (int) – The number of days the change is calculated over.

• weeks (int) – The number of weeks the change is calculated over.

• months (int) – The number of months the change is calculated over.

• years (int) – The number of years the change is calculated over.

• relative (bool) – If True, the change is calculated as relative change (i.e. a/b-1). If False, the change is calculated as a difference (i.e. a-b).

Example:

Suppose a company has a standard fiscal calendar (ending 31 December), and you want to calculate, for each month, how much the sales revisions have changed over the past three months for the fiscal year containing the given month. You can then use the expression

fs_revisions_change('sales', period='GY1', freq='M', months=3)

In this case, the values are calculated as follows:

The value on	Calculation
31 Dec 2023	The revision for FY-2023 on 31 Dec 2023 relative to the revision on 30 Sep 2023
31 Jan 2024	The revision for FY-2024 on 31 Jan 2024 relative to the revision on 31 Oct 2023

Data items

These are the data items that can be used in any of the FactSet signals listed on this page. These are case-insensitive.

Basic items:

• EPS – Earnings Per Share

• EPS_C – Consolidated EPS

• EPS_P – Standalone Earnings Per Share

• SALES – Sales

• SALES_C – Consolidated Sales

• SALES_P – Standalone Sales

• DPS – Declared Dividend Per Share

• CFPS – Cash Flow Per Share

Advanced items:

• AFFO – Adjusted Funds From Operations

• APP_CAP_RATE – Applied Capital Rate

• ASP – Average Selling Price

• ASSETS – Total Assets

• BFNG – Net Income Reported

• BPS – Book Value Per Share

• BPS_TANG – Tangible Book Value Per Share

• CAPEX – Capital Expenditure

• CASH_NP – Cash Net Income

• CASH_NP_CONT – Cash Net Income from Continuing Operations

• CASH_ST – Cash and Cash Equivalents

• CCUR_GRTH – Constant Currency Revenue Growth

• CF_FIN – Cash Flow From Financing

• CF_INV – Cash Flow From Investing

• CF_OP – Cash Flow From Operations

• CFO_GAAP – Cash Flow from Operations – GAAP

• COS – Cost of Sales

• CURRENT_ASSETS – Current Assets

• CURRENT_LIABILITIES – Current Liabilities

• DCF – Distributable Cash Flow

• DCFLP – Distributable Cash Flow to Limited Partners

• DCFPU – Distributable Cash Flow Per Unit

• DCFPULP – Distributable Cash Flow Per Unit to Limited Partners

• DEBT_LT – Long Term Debt

• DEBT_ST – Short–Term Debt

• DEFREVENUE – Total Deferred Revenue

• DEFREVENUE_LT – Deferred Revenue Long Term

• DEFREVENUE_ST – Deferred Revenue Short Term

• DEPR_AMORT – Depreciation and Amortization

• DISCR_CF – Discretionary Cash Flow

• EBIT – EBIT

• EBIT_ADJ – EBIT Adjusted

• EBIT_C – Consolidated EBIT

• EBIT_P – Standalone EBIT

• EBITA – EBITA

• EBITDA – EBITDA

• EBITDA_ADJ – EBITDA Adjusted

• EBITDA_REP – EBITDA Reported

• EBITDAR – EBITDAR

• EBITDAX – EBITDA including Exploration Expense

• EBITR – EBIT Reported

• EPS_EX_XORD – Earnings Per Share Excluding Exceptionals

• EPS_GAAP – Reported Earnings Per Share

• EPS_NONGAAP – Earnings Per Share-Non-GAAP

• EPSAD – Diluted Adjusted EPS

• EPSRD – Diluted Reported EPS

• EUR_JPY – Forex – EUR per JPY

• FCF – Free Cash Flow

• FCFPS – Free Cash Flow Per Share

• FFO – Funds From Operations

• G_A_EXP – General and Administrative Expense

• GMV – Gross Merchandise Volume

• GW_TOT – Total Goodwill

• HEPSB – Headline Basic EPS

• HEPSD – Headline Diluted EPS

• INC_GROSS – Gross Income

• INT_EXP – Interest Expense

• INTANG – Intangible Assets

• INVENTORIES – Inventories

• LCUR_GRTH – Local Currency Revenue Growth

• MAINT_CAPEX – Maintenance CAPEX

• MINTEREST – Minority Interest

• NDT – Net Debt

• NET – Net Profit

• NET_C – Consolidated Net Income

• NET_P – Standalone Net Income

• NET_SALES – Net Sales

• NETBG – Net Profit Adjusted

• OP_RATIO – Operating Ratio

• ORGANICGROWTH – Organic Growth

• PAY_ACCT – Accounts Payable

• PTI – Pre-Tax Profit

• PTI_C – Consolidated Pretax Income

• PTIAG – Pre-Tax Profit Reported

• PTP_P – Standalone Pretax Income

• PTPA – Pre-Tax Income Adjusted

• RD_EXP – Research and Development

• RECEIV_NET – Accounts Receivable

• REV_TOT – Total Revenues

• S_M_EXP – Selling and Marketing Expense

• SGA – Selling, General and Administrative Expense

• SH_EQUITY – Shareholder’s Equity

• SHS_REPURCH – Share Repurchase

• SOE – Stock Option Expense

• SS_NOI – Same Store Net Operating Income

• TAX_EXPENSE – Tax Expense

• TOTAL_DEBT – Total Debt

• UFCF – Unlevered Free Cash Flow

• USD_JPY – Forex – USD per JPY

• WKCAP – Working Capital

Industry items:

• ACCESS_LINES – Access Lines

• ARPU – Average Revenue Per User

• ASSETS_NONPERF – Non-Performing Assets

• ASSETS_RISK_WGHT – Risk Weighted Assets

• ASV – Annual Subscription Value

• AUM – Assets Under Management

• AUM_AVG – Assets Under Management Average

• AVAILABLESEATKM – Available seat km (ASK)

• AVG_EARN_ASSETS – Average Earning Assets

• BACKLOG_AVG_PRICE – Backlog Average Price

• BACKLOG_UNITS – Backlog Units

• BACKLOG_VALUE – Backlog Value

• BAD_DEBT_PROV – Provision for Bad Debt

• BVPS_EXCL_AOCI – Book Value Per Share Excl AOCI

• BVPS_INCL_AOCI – Book Value Per Share Incl AOCI

• CANCELRATE – Cancellation Rate

• CAP_RATIO_TIER1 – Tier 1 Capital Ratio

• CASH_COST – Cash Cost

• CHEM_DOM – Chemicals Income - Domestic

• CHEM_INTL – Chemicals Income - International

• CHEM_NETINC – Chemicals Post Taxes

• CHEM_OPINC – Chemicals Income

• CHURN – Churn

• CLAIMS_EXP – Claims Expense

• COMB_RATIO_UND – Underlying Combined Ratio

• COMBINED_RATIO – Combined Ratio

• COMCAP_RATIO_TIER1 – Tier 1 Common Capital Ratio

• CONTR_PROF – Contribution Profit

• COST_INCOME – Cost to Income Ratio

• COST_PER_GRAM – Marijuana

• CPGA – Cost per Gross Add

• DACF – Debt-Adjusted Cash Flow

• DAU – Daily Active Users

• DELIV_PRICE – Deliveries Average Price

• DELIVERIES_UNITS – Deliveries Units

• DEPS – Deposits

• DEPS_AVG – Average Deposits

• E_P_DOM – Upstream Income - Domestic

• E_P_INTL – Upstream Income - International

• E_P_NETINC – Upstream Post Taxes

• E_P_NETINC_DOM – Upstream Post Taxes - Dom

• E_P_OPINC – Upstream Income

• EMBEDDED_VALUE – Embedded Value

• EXPENSE_RATIO – Expense Ratio

• EXPL_EXP – Exploration Expenses

• FEE_AUM – Fee AUM - EOP

• FEES – Fees

• FFO_REP – Reported Funds from Operations

• FIN_SERVICES – Financial Services

• FRE – Fee Related Earnings

• GROSS_ADDS – Gross Adds

• GROSS_PREM_WRITTEN – Gross Premiums Written

• HOME_SALES – Home Sales

• IMP_CAP_RATE – Implied Cap Rate

• INC_FEES – Income from Fees & Commissions

• INC_TRADING – Trading Income

• INT_INC – Net Interest Income

• INT_INC_MARGIN – Net Interest Margin

• INVEST_INC – Net Investment Income

• KG_CANNABIS_SOLD – Marijuana

• LAND_SALES – Land Sales

• LIFE_INS_CLAIMS – Life Insurance Claims

• LOADFACTOR – Load Factor

• LOAN_NET – Net Loans

• LOAN_NET_AVG – Average Net Loans

• LOAN_NONPERF – Non-Performing Loans (NPL)

• LOAN_PROV – Provisions for Loans

• LOSS_RATIO – Loss Ratio

• LT_FLOWS – Long Term Flows

• LTV – Loan to Value

• M_REV_USER – Monthly Revenue Per User

• MAU – Monthly Active Users

• MCR – Medical Cost Ratio

• MOU – Minutes of Use

• MUU – Monthly Unique Users

• NAVPS – Net Asset Value Per Share

• NET_ADDS – Net Adds

• NET_CHARGE_OFFS – Net Charge-Offs

• NETFLOWS – Net Flows

• NEW_ORD_PRICE – New Orders Average Price

• NEW_ORDERS_UNITS – New Orders Units

• NEW_ORDERS_VALUE – New Orders Value

• NON_INT_INC – Non-Interest Income

• NPE_LIFE – Net Premiums Earned - Life

• NPE_PC – Net Premiums Earned - P&C

• NPW_LIFE – Net Premiums Written - Life

• OCCUPY_RATE_DOM – Occupancy Rate - Domestic

• OCCUPY_RATE_INTL – Occupancy Rate - International

• OCCUPY_RATE_TOT – Occupancy Rate - Total

• OPER_EXP – Operating Expense

• OPEX_ASK – Operating Expenses per ASK

• OPEX_ASK_XFUEL – Operating Expenses per ASK excluding fuel costs

• OPEX_UNIT – OPEX per Unit

• OTHER_OPEX – Other Operating Expenses

• PAIDNADDS – Paid Net Adds

• PASS_REV_ASK – Passenger revenue per ASK

• PASS_REV_RPK – Passenger revenue per RPK

• PREM_EARN – Net Premiums Earned

• PREM_WRITTEN – Net Premiums Written

• PRICE_BRENT – Brent Price

• PRICE_CA_LIGHT – Canadian Light Oil Price

• PRICE_DUBAI_OIL – Dubai Crude Price

• PRICE_ED_OIL – Edmonton Par Oil Price

• PRICE_SCO – Synthetic Crude Price

• PROD_DAY_GAS – Production per day - Natural Gas

• PROD_DAY_NGL_ONLY – Production Per Day - NGLs

• PROD_DAY_OIL – Production per day - Oil & NGLs

• PROD_DAY_OIL_ONLY – Production Per Day - Oil

• PROD_OIL_SANDS – Total Production - OIL Sands

• PRODPERDAY – Production per day

• R_M_DOM – Downstream Income - Domestic

• R_M_INTL – Downstream Income - International

• R_M_NETINC_INTL – Downstream Post Taxes - Intl

• R_M_OPINC – Downstream Income

• REAL_PRICE – Realized Price

• REAL_PRICE_GAS – Realized Price - Natural Gas

• REAL_PRICE_M – Realized Price - Mining

• REAL_PRICE_OG – Realized Price - Oil and Gas

• REAL_PRICE_OIL – Realized Price - Oil & NGLs

• REALP_GAS_NGL – Realized Price - Gas & NGLs

• REV_PASSENGER – Revenue passenger

• REV_PER_ROOM_DOM – Revenue per Available Room (RevPar) - Domestic

• REV_PER_ROOM_INTL – Revenue per Available Room (RevPar) - International

• REV_PER_ROOM_TOT – Revenue per Available Room (RevPar) - Total

• REV_UNIT – Revenue Per Unit

• REVPASSENGERKM – Revenue passenger km (RPKs)

• RNAVPS – Net Asset Value Per Share - Next Twelve Months (NAV-NTM)

• ROOM_RATE_DAILY_DOM – Daily Room Rate (ADR) - Domestic

• ROOM_RATE_DAILY_INTL – Daily Room Rate (ADR) - International

• ROOM_RATE_DAILY_TOT – Daily Room Rate (ADR) - Total

• RSV_1P – 1P Proved Reserves

• RSV_2P – 2P Proved and Probable Reserves

• RSV_3P – 3P Proved Probable and Possible Reserves

• SAC – Subscriber Acquisition Cost

• SAL_BENEFITS – Salaries and Benefits

• SALES_RSF – Net sales per square foot

• SAMESTORESALES – Same Stores Sales - Total

• SELL_SP – Selling Space - Total

• SELL_SP_D – Selling Space - Domestic

• SELL_SP_I – Selling Space - International

• SS_ADJ_ADM – Same Store Adjusted Admissions

• SS_ADM – Same Store Admissions

• SS_REV_PER_ADJ_ADM – Same Store Revenue per Adjusted Admissions

• SSS_D – Same Stores Sales - Domestic

• SSS_I – Same Stores Sales - International

• ST_CL – Number of Stores Closed - Total

• ST_CL_D – Number of Stores Closed - Domestic

• ST_CL_I – Number of Stores Closed - International

• ST_END – Number of Stores at Period End - Total

• ST_END_D – Number of Stores at Period End - Domestic

• ST_END_I – Number of Stores at Period End - International

• ST_OPN_D – Number of Stores Opened - Domestic

• ST_OPN_I – Number of Stores Opened - International

• ST_RLOC – Number of Stores Relocated - Total

• ST_RLOC_D – Number of Stores Relocated - Domestic

• ST_RLOC_I – Number of Stores Relocated - International

• STOREN_OPENED – Number of Stores Opened - Total

• STUDENTENROLL_NEW – New Student Enrollment

• STUDENTENROLL_TOT – Total Student Enrollment

• SUBSCRIBERS_NB – Number of Subscribers

• SUPPLIES – Supplies Cost

• TAM – Total Addressable Market

• TOT_REV_ASK – Total Revenue per ASK

• TOTAL_PROD – Total Production

• TOTAL_PROD_M – Total Production - Mining

• TOTAL_PROD_OG – Total Production - Oil and Gas

• UW_INCOME – Underwriting Income

• VOL_GRTH – Volume Growth