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
orLTM
.alignment – An alignment:
afp
,fp
,pd
orrd
.currency (str) – Optionally, a three-letter currency code (e.g.
USD
orEUR
). 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
orFY
.alignment – An alignment:
afp
,fp
,pd
orrd
.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
orEUR
). 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 therelative_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 argumentrelative_to
to be set. The default value is 0. Ifrelative_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
orFY
.alignment – An alignment:
afp
,fp
,pd
orrd
.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
orEUR
). 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 therelative_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 argumentrelative_to
to be set. The default value is 0. Ifrelative_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. Eitherblended
(default),last
ornearest
. 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. EitherFQ/FS
,FQ
,FS
orFY
. Ifperiod
specifies a calendar year, the default isFQ/FS
, if it specifies a quarter, the default isFQ
, and if it specifies a semi-annual period, the default isFS
.
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:
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.)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
.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
andyears
must be specified.- Parameters:
parameter (str) – A FactSet estimates data item.
period (str) – A rolling fiscal period. The supported options are
GYn
,GQn
,GSn
andGQ/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) andD
(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 ShareEPS_C
– Consolidated EPSEPS_LTG
– Long Term GrowthEPS_P
– Standalone Earnings Per ShareSALES
– SalesSALES_C
– Consolidated SalesSALES_P
– Standalone SalesDPS
– Declared Dividend Per ShareCFPS
– Cash Flow Per Share
Advanced items:
AFFO
– Adjusted Funds From OperationsAPP_CAP_RATE
– Applied Capital RateARR
– Annual Recurring RevenueASP
– Average Selling PriceASSETS
– Total AssetsBFNG
– Net Income ReportedBOOK_ROE
– Book Return on EquityBPS
– Book Value Per ShareBPS_TANG
– Tangible Book Value Per ShareBROAD_ARPU
– Broadband ARPUBUILD_IMPROV
– Building and Improvement, NetCAPEX
– Capital ExpenditureCASH_NOI
– Cash Net Operating IncomeCASH_NP
– Cash Net IncomeCASH_NP_CONT
– Cash Net Income from Continuing OperationsCASH_ST
– Cash and Cash EquivalentsCCUR_GRTH
– Constant Currency Revenue GrowthCF_FIN
– Cash Flow From FinancingCF_INV
– Cash Flow From InvestingCF_OP
– Cash Flow From OperationsCFO_GAAP
– Cash Flow from Operations - GAAPCOS
– Cost of SalesCOS_DEBT
– Cost of Debt (%)CURRENT_ASSETS
– Current AssetsCURRENT_LIABILITIES
– Current LiabilitiesDCF
– Distributable Cash FlowDCFLP
– Distributable Cash Flow to Limited PartnersDCFPU
– Distributable Cash Flow Per UnitDCFPULP
– Distributable Cash Flow Per Unit to Limited PartnersDEBT_LT
– Long Term DebtDEBT_ST
– Short-Term DebtDEFREVENUE
– Total Deferred RevenueDEFREVENUE_LT
– Deferred Revenue Long TermDEFREVENUE_ST
– Deferred Revenue Short TermDEPR_AMORT
– Depreciation and AmortizationDEVELOP_PROP
– Development PropertiesDISCR_CF
– Discretionary Cash FlowEBIT
– EBITEBIT_ADJ
– EBIT AdjustedEBIT_C
– Consolidated EBITEBIT_P
– Standalone EBITEBITA
– EBITAEBITDA
– EBITDAEBITDA_ADJ
– EBITDA AdjustedEBITDA_C
– Consolidated EBITDAEBITDA_P
– Standalone EBITDAEBITDA_REP
– EBITDA ReportedEBITDAR
– EBITDAREBITDAX
– EBITDA including Exploration ExpenseEBITR
– EBIT ReportedEPS_EX_XORD
– Earnings Per Share Excluding ExceptionalsEPS_GAAP
– Reported Earnings Per ShareEPS_NONGAAP
– Earnings Per Share-Non-GAAPEPSAD
– Diluted Adjusted EPSEPSRD
– Diluted Reported EPSEQ_RATIO
– Equity Ratio (%)EQUITY_INV
– Total Equity Securities InvestmentEUR_JPY
– Forex - EUR per JPYFCF
– Free Cash FlowFCFPS
– Free Cash Flow Per ShareFFO
– Funds From OperationsFFO_DEBT
– FFO_DEBT (%)FIXED_INCOME_INV
– Total Fixed Income Securities InvestmentG_A_EXP
– General and Administrative ExpenseGMV
– Gross Merchandise VolumeGPW_LIFE
– Gross Premiums Written - LifeGPW_PC
– Gross Premiums Written - P&CGW_TOT
– Total GoodwillHEPSB
– Headline Basic EPSHEPSD
– Headline Diluted EPSINC_GROSS
– Gross IncomeINS_EQ_POL
– SurrendersINS_RSRV
– Insurance ReservesINT_COVER_RATIO
– Interest Coverage Ratio (X)INT_EXP
– Interest ExpenseINTANG
– Intangible AssetsINVENTORIES
– InventoriesINVEST_ASSETS
– Invested AssetsINVEST_INC_LIFE
– Net Investment Income - LifeINVEST_INC_PC
– Net Investment Income - P&CLAND
– LandLAND_HFD
– Land Held for DevelopmentLCUR_GRTH
– Local Currency Revenue GrowthMAINT_CAPEX
– Maintenance CAPEXMINTEREST
– Minority InterestMTGP
– Annual Avgerage Target PriceNBEQUITIES
– Number of EquitiesNDT
– Net DebtNET
– Net ProfitNET_C
– Consolidated Net IncomeNET_P
– Standalone Net IncomeNET_SALES
– Net SalesNETBG
– Net Profit AdjustedNPW_PC
– Net Premiums Written - P&COP_RATIO
– Operating RatioORGANICGROWTH
– Organic GrowthPAY_ACCT
– Accounts PayablePENS_BENF
– Pension & BenefitsPRIOR_YR_DEV
– Prior Year DevelopmentPTI
– Pre-Tax ProfitPTI_C
– Consolidated Pretax IncomePTIAG
– Pre-Tax Profit ReportedPTP_P
– Standalone Pretax IncomePTPA
– Pre-Tax Income AdjustedRD_EXP
– Research and DevelopmentRECEIV_NET
– Accounts ReceivableREV_TOT
– Total RevenuesS_M_EXP
– Selling and Marketing ExpenseSAME_STORE_NOI
– Same Store NOISGA
– Selling, General and Administrative ExpenseSH_EQUITY
– Shareholder’s EquitySHS_REPURCH
– Share RepurchaseSOE
– Stock Option ExpenseSS_NOI
– Same Store Net Operating IncomeTAX_EXPENSE
– Tax ExpenseTOTAL_CAPITAL
– Total CapitalTOTAL_DEBT
– Total DebtTOTAL_RPO
– Total RPOTPV
– Total Payment VolumeUFCF
– Unlevered Free Cash FlowUNITS
– Units (millions)USD_JPY
– Forex - USD per JPYUW_EXP
– Underwriting ExpenseUW_INCOME_LIFE
– Underwriting Income - LifeUW_INCOME_PC
– Underwriting Income - P&CWIRELES_ARPU
– Wireless ARPUWKCAP
– Working Capital
Industry items:
ACCESS_LINES
– Access LinesACQUI_NOI
– Acquisition NOIARPU
– Average Revenue Per User (ARPU)ASSETS_NONPERF
– Non-Performing AssetsASSETS_RISK_WGHT
– Risk Weighted Assets (RWA)ASV
– Annual Subscription Value (ASV)AUC_EOP
– Assets Under Custody End of PeriodAUM
– Assets Under Management (AUM)AUM_AVG
– Assets Under Management AverageAVAILABLESEATKM
– Available seat km (ASK)AVG_EARN_ASSETS
– Average Earning AssetsBACKLOG_AVG_PRICE
– Backlog Average PriceBACKLOG_UNITS
– Backlog UnitsBACKLOG_VALUE
– Backlog ValueBAD_DEBT_PROV
– Provision for Bad DebtBENEFIT_RATIO
– Benefit Ratio (%)BOLI
– Bank Owned Life InsuranceBUSINESS_ARPU
– Business Services ARPUBVPS_EXCL_AOCI
– Book Value Per Share Excl AOCIBVPS_INCL_AOCI
– Book Value Per Share Incl AOCICANCELRATE
– Cancellation RateCAP_RATIO_TIER1
– Tier 1 Capital RatioCAP_RATIO_TOT
– Total Capital Ratio (%)CARD_INCOME
– Card IncomeCASH_CONV
– Cash Conversion (FCF/NetProfit) (%)CASH_COST
– Cash CostCAT_LOSSES
– Cat LossesCAT_LOSSES_RATIO
– Cat Losses (%)CHEM_DOM
– Chemicals Income - DomesticCHEM_INTL
– Chemicals Income - InternationalCHEM_NETINC
– Chemicals Post TaxesCHEM_NETINC_DOM
– Chemicals Post Taxes - DomCHEM_NETINC_INTL
– Chemicals Post Taxes - IntlCHEM_OPINC
– Chemicals IncomeCHG_CASH_CF
– Net Change in CashCHURN
– ChurnCLAIMS_EXP
– Claims ExpenseCOMB_RATIO_UND
– Underlying Combined RatioCOMBINED_RATIO
– Combined RatioCOMCAP_RATIO_TIER1
– Tier 1 Common Capital RatioCOM_EQUITY_TIER1
– Common Equity Tier 1 (CET1)CONTR_PROF
– Contribution ProfitCORE_FFO
– Core Funds from OperationsCOST_INCOME
– Cost to Income RatioCOST_PER_GRAM
– MarijuanaCPGA
– Cost per Gross AddCURRENT_RPO
– Current RPOCURRENT_RPO_BOOKINGS
– Current RPO BookingsCUS_REL_ARPU
– Customer Relationship ARPUDACF
– Debt-Adjusted Cash Flow (DACF)DAU
– Daily Active UsersDEFACQUI_COST
– Deferred Acquisition CostDELIV_PRICE
– Deliveries Average PriceDELIVERIES_UNITS
– Deliveries UnitsDEPS
– DepositsDEPS_AVG
– Average DepositsDEV_NOI
– Development Net Operating IncomeDFD_TAX_CR
– Deferred Income Taxes - LiabilitiesDFD_TAX_DB
– Deferred Income Taxes - AssetsDFD_TAX_XITC_CF
– Deferred Income Taxes - Cash FlowDISPO_NOI
– Disposition NOIE_P_DOM
– Upstream Income - DomesticE_P_INTL
– Upstream Income - InternationalE_P_NETINC
– Upstream Post TaxesE_P_NETINC_DOM
– Upstream Post Taxes - DomE_P_NETINC_INTL
– Upstream Income International, Post TaxesE_P_OPINC
– Upstream IncomeEMBEDDED_VALUE
– Embedded ValueEQUIP_EXP
– Occupancy & Equipment ExpenseEXPENSE_RATIO
– Expense RatioEXPL_EXP
– Exploration ExpensesFDIC
– FDIC Insurance expenseFEE_AUM
– Fee AUM - EOPFEES
– FeesFFO_REP
– Reported Funds from OperationsFIN_SERVICES
– Financial ServicesFOREX_OTHERTRAD
– Foreign Exchange and Other Trading RevenueFRE
– Fee Related EarningsFUEL
– Fuel CostsFUEL_PURCH_POWER
– Fuel, Purchased Power CostsGROSS_ADDS
– Gross AddsGROSS_PREM_WRITTEN
– Gross Premiums WrittenHIS_ARPU
– High Speed Internet ARPUHOME_SALES
– Home SalesIMP_CAP_RATE
– Implied Cap RateINC_FEES
– Income from Fees & CommissionsINC_TRADING
– Trading IncomeINS_INC
– Insurance CommissionsINT_INC
– Net Interest IncomeINT_INC_MARGIN
– Net Interest MarginINV_BANK_TRUST
– Investment Banking & TrustINV_MNGT_FEES
– Investment Management FeesINV_SERV_FEES
– Investment Services FeesINVEST_INC
– Net Investment IncomeINVEST_PROP
– Investment PropertiesKG_CANNABIS_SOLD
– MarijuanaLAND_SALES
– Land SalesLEND_DEPS_FEE
– Lending & Deposit Related FeesLEV_RATIO_TIER1
– Tier 1 Leverage Ratio (%)LIABS_SHLDRS_EQ
– Total Liabilities and EquityLIFE_INS_CLAIMS
– Life Insurance ClaimsLOADFACTOR
– Load FactorLOAN_LOSS_RSRV
– Loan Loss ReserveLOAN_NET
– Net LoansLOAN_NET_AVG
– Average Net LoansLOAN_NONPERF
– Non-Performing Loans (NPL)LOANOREO_NONPERF
– NPAs/Loan+OREO (%)LOAN_PROV
– Provisions for LoansLOSS_RATIO
– Loss RatioLOSS_RATIO_UND
– Underlying Loss Ratio (%)LT_FLOWS
– Long Term FlowsLTV
– Loan to ValueM_REV_USER
– Monthly Revenue Per UserMAU
– Monthly Active UsersMCR
– Medical Cost RatioMORTGAGE_BANKING
– Mortgage BankingMOU
– Minutes of UseMUU
– Monthly Unique UsersNAVPS
– Net Asset Value Per Share (NAVPS)NET_ADDS
– Net AddsNET_CHARGE_OFFS
– Net Charge-OffsNET_INVEST_YIELD
– Net Investment Yield (%)NETFLOWS
– Net FlowsNEW_ORD_PRICE
– New Orders Average PriceNEW_ORDERS_UNITS
– New Orders UnitsNEW_ORDERS_VALUE
– New Orders ValueNON_COMP_EXP
– Non-Compensation ExpenseNON_CURRENT_RPO
– Non Current RPONON_INT_INC
– Non-Interest IncomeNPE_LIFE
– Net Premiums Earned - LifeNPE_PC
– Net Premiums Earned - P&CNPW_LIFE
– Net Premiums Written - LifeOCCUPY_EXP
– Occupancy ExpenseOCCUPY_RATE_DOM
– Occupancy Rate - DomesticOCCUPY_RATE_INTL
– Occupancy Rate - InternationalOCCUPY_RATE_TOT
– Occupancy Rate - TotalOPER_EXP
– Operating ExpenseOPEX_ASK
– Operating Expenses per ASKOPEX_ASK_XFUEL
– Operating Expenses per ASK excluding fuel costsOPEX_UNIT
– OPEX per UnitOREO_EXP
– Other Real Estate Owned ExpenseOTHER_OPEX
– Other Operating ExpensesPAIDNADDS
– Paid Net AddsPASS_REV_ASK
– Passenger revenue per ASKPASS_REV_RPK
– Passenger revenue per RPKPFD_STK
– Preferred EquityPOSTPAID_ARPU
– Wireless Postpaid ARPUPOSTPAID_PH_ARPU
– Postpaid Phone ARPUPPE_EXP
– Equipment ExpensePREM_EARN
– Net Premiums EarnedPREM_WRITTEN
– Net Premiums WrittenPREPAID_ARPU
– Wireless Prepaid ARPUPRICE_BRENT
– Brent PricePRICE_CA_LIGHT
– Canadian Light Oil PricePRICE_DUBAI_OIL
– Dubai Crude PricePRICE_ED_OIL
– Edmonton Par Oil PricePRICE_SCO
– Synthetic Crude PricePRICE_URALS
– Urals Crude PricePRICE_WCS
– Western Canadian Select Crude PricePRICE_WTI
– West Texas Intermediate PricePROD_ALUM
– Total Production Aluminium (t)PROD_ALUN
– Total Production Alumina (t)PROD_BAUX
– Total Production Bauxite (t)PROD_BORATES
– Total Production Borates (t)PROD_CATH
– Total Production Copper Cathode (t)PROD_CHROMEORE
– Total Production Chrome Ore (t)PROD_COAL
– Total Production Coal (t)PROD_COBALT
– Total Production Cobalt (t)PROD_COBCON
– Total Production Cobalt Concentrate (t)PROD_COKE
– Total Production Coke (t)PROD_COPP
– Total Production Copper (t)PROD_COPPCON
– Total Production Copper Concentrate (t)PROD_COPPREFINED
– Total Production Copper Refined (t)PROD_COPPSMELT
– Total Production Copper Smelting (t)PROD_COSTS
– Production CostsPROD_CRUDESTEEL
– Total Production Crude Steel (t)PROD_DAY_GAS
– Production per day - Natural GasPROD_DAY_GAS_NGL
– Production Per Day - Natural Gas & NGLsPROD_DAY_NGL_ONLY
– Production Per Day - NGLsPROD_DAY_OIL
– Production per day - Oil & NGLsPROD_DAY_OIL_ONLY
– Production Per Day - OilPROD_DIAM
– Total Production Diamonds (ct)PROD_FERROCHROME
– Total Production Ferro Chrome (t)PROD_GAS
– Total Production - Natural Gas (mmcf)PROD_GOLD
– Total Production Gold (oz)PROD_GOLDCON
– Total Production Gold Concentrate (oz)PROD_GOLDSMELT
– Total Production Gold Smelting (t)PROD_HARDCOAL
– Total Production Hard Coking Coal (t)PROD_ILMENITE
– Total Production Ilmenite (t)PROD_IRON
– Total Production Iron Ore (t)PROD_IRONORECON
– Total Production Iron Ore Concentrate (t)PROD_LEAD
– Total Production Lead (t)PROD_LEADCON
– Total Production Lead Concentrate (t)PROD_LEADSMELT
– Total Production Lead Smelting (t)PROD_MANGALLOY
– Total Production Manganese Alloy (t)PROD_MANGORE
– Total Production Manganese Ore (t)PROD_MELTSHOP
– Total Production Melt Shop (t)PROD_MET
– Total Production Metallurgical Coal (t)PROD_MOLY
– Total Production Molybdenum (t)PROD_NGL
- Total Production - Natural Gas Liquids (mmbbl)PROD_NICK
– Total Production Nickel (t)PROD_NICKCON
– Total Production Nickel Concentrate (t)PROD_OIL
– Total Production - OIL (mmbbl)PROD_OIL_NGL
– Total Production - OIL & NGL (mmbbl)PROD_OIL_SANDS
– Total Production - OIL SandsPROD_PALLA
– Total Production Palladium (oz)PROD_PELLETS
– Total Production Pellets (t)PROD_PLAT
– Total Production Platinum (oz)PROD_RAWCOAL
– Total Production Raw Coal (mt)PROD_RHOD
– Total Production Rhodium (oz)PROD_RUTILE
– Total Production Rutile (t)PROD_SEMISOFT
– Total Production Semi Soft Coking Coal (t)PROD_SILV
– Total Production Silver (oz)PROD_SILVCON
– Total Production Silver Concentrate (oz)PROD_SILVSMELT
– Total Production Silver Smelting (t)PROD_STEEL
– Total Production Steel (t)PROD_SULPHACID
– Total Production Sulphuric Acid (t)PROD_SYNTHRUTILE
– Total Production Synthetic Rutile (t)PROD_THERCOAL
– Total Production Thermal Coal (t)PROD_THERCOALEPT
– Total Production Thermal Coal Export (t)PROD_TIO2
– Total Production Titanium Dioxide (t)PROD_TITAN
– Total Production Titanium (t)PROD_URAN
– Total Production Uranium (t)PROD_ZINC
– Total Production Zinc (t)PROD_ZINCCON
– Total Production Zinc Concentrate (t)PROD_ZINCREFINED
– Total Production Zinc Refined (t)PROD_ZINCSMELT
– Total Production Zinc Smelting (t)PROD_ZIRCON
– Total Production Zircon (t)PRODPERDAY
– Production per dayPROF_FEES_EXP
– Professional FeesPURCH_POWER
– Purchased PowerR_M_DOM
– Downstream Income - DomesticR_M_INTL
– Downstream Income - InternationalR_M_NETINC
– Downstream Income Post TaxesR_M_NETINC_DOM
– Downstream Income Post Taxes - DomR_M_NETINC_INTL
– Downstream Post Taxes - IntlR_M_OPINC
– Downstream IncomeRE_SS_OPER_EXP
– Same Store ExpenseRE_SS_REV
– Same Store RevenueREAL_PRICE
– Realized PriceREAL_PRICE_BH
– Realized Price - Before HedgesREAL_PRICE_GAS
– Realized Price - Natural GasREAL_PRICE_M
– Realized Price - MiningREAL_PRICE_OG
– Realized Price - Oil and GasREAL_PRICE_OIL
– Realized Price - Oil & NGLsREALP_GAS_BH
– Realized Price - Natural Gas Before HedgesREALP_GAS_NGL
– Realized Price - Gas & NGLsREALP_NGL
– Realized Price - Natural Gas LiquidsREALP_NGL_BH
– Realized Price - NGLs Before HedgesREALP_OIL_BH
– Realized Price - Oil Before HedgesREALP_OIL_NGL
– Realized Price - Oil & NGLsREALP_OIL_NGL_BH
– Realized Price - Oil & NGLs Before HedgesRESIDENT_ARPU
– Residential Customer ARPURESI_DATA_ARPU
– Residential Data ARPURESI_VIDEO_ARPU
– Residential Video ARPURESI_VOICE_ARPU
– Residential Voice ARPUREST_MARG
– Restaurant Margin (%)RETAIL_ARPU
– Retail Wireless ARPUREV_PASSENGER
– Revenue passengerREV_PER_ROOM_DOM
– Revenue per Available Room (RevPar) - DomesticREV_PER_ROOM_INTL
– Revenue per Available Room (RevPar) - InternationalREV_PER_ROOM_TOT
– Revenue per Available Room (RevPar) - TotalREV_UNIT
– Revenue Per UnitREVPASSENGERKM
– Revenue passenger km (RPKs)RISK_BASED_CAP
– Total Risk-based CapitalRNAVPS
– Net Asset Value Per Share - Next Twelve Months (NAV-NTM)ROOM_RATE_DAILY_DOM
– Daily Room Rate (ADR) - DomesticROOM_RATE_DAILY_INTL
– Daily Room Rate (ADR) - InternationalROOM_RATE_DAILY_TOT
– Daily Room Rate (ADR) - TotalROTE
– Return on Tangible Equity (%)RSRV_BUILD
– Reserve BuildRSV_1P
– 1P Proved ReservesRSV_2P
– 2P Proved and Probable ReservesRSV_3P
– 3P Proved Probable and Possible ReservesSAC
– Subscriber Acquisition CostSAL_BENEFITS
– Salaries and BenefitsSALES_RSF
– Net sales per square footSAMESTORESALES
– Same Stores Sales - TotalSAMESTORESALESM
– Same Store Sales Monthly (%)SELL_SP
– Selling Space - TotalSELL_SP_D
– Selling Space - DomesticSELL_SP_I
– Selling Space - InternationalSERVICE_CHRG
– Service Charges on DepositsSOFT_PROC_FEES
– Software and Processing FeesSS_ADJ_ADM
– Same Store Adjusted AdmissionsSS_ADM
– Same Store AdmissionsSS_EXP_GR
– Same Store Expense growth (%)SS_REV_PER_ADJ_ADM
– Same Store Revenue per Adjusted AdmissionsSSS_D
– Same Stores Sales - DomesticSSS_I
– Same Stores Sales - InternationalST_CL
– Number of Stores Closed - TotalST_CL_D
– Number of Stores Closed - DomesticST_CL_I
– Number of Stores Closed - InternationalST_END
– Number of Stores at Period End - TotalST_END_D
– Number of Stores at Period End - DomesticST_END_I
– Number of Stores at Period End - InternationalST_OPN_D
– Number of Stores Opened - DomesticST_OPN_I
– Number of Stores Opened - InternationalST_RLOC
– Number of Stores Relocated - TotalST_RLOC_D
– Number of Stores Relocated - DomesticST_RLOC_I
– Number of Stores Relocated - InternationalSTOREN_OPENED
– Number of Stores Opened - TotalSTUDENTENROLL_NEW
– New Student EnrollmentSTUDENTENROLL_TOT
– Total Student EnrollmentSUBSCRIBERS_NB
– Number of SubscribersSUBSVIDEO_ARPU
– Subscription Video ARPUSUPPLIES
– Supplies CostTAM
– Total Addressable MarketTAXES_NON_INC
– Taxes Other Than IncomeTCE_TA
– Tangible Common Equity/Tangible Assets (%)TEXAS_RATIO
– Texas Ratio (%)TIER1_CAP
– Tier 1 CapitalTOT_CAPACITY_MW
– Total Capacity (Mw)TOT_OREO
– Total Other Real Estate OwnedTOT_REV_ASK
– Total Revenue per ASKTOTAL_PROD
– Total ProductionTOTAL_PROD_M
– Total Production - MiningTOTAL_PROD_OG
– Total Production - Oil and GasTOTAL_RPO_BOOKINGS
– Total RPO BookingsTRANS_PROC_SERV
– Transaction Processing ServicesTRUST_INC
– Trust and Asset Management IncomeUW_INCOME
– Underwriting IncomeVIDEOADVERT_ARPU
– Video Advertising ARPUVIDO_ARPU
– Video ARPUVOICE_ARPU
– Voice ARPUVOL_GRTH
– Volume GrowthWHOLESAL_ARPU
– Wholesale Wireless ARPU