FF_ExtractDataSnapshot

Transcription

1 FF_ExtractDataSnapshot The ExtractDataSnapshot function is used for extracting in MATLAB multiple items for a list of ids for 1 date, availble for equity, fixed income and funds. This function is using FactSet Screening Language. The FactSet Screening Language is a way to efficiently extract data for a large universe of securities as of a single date. The data can also be retrieved using a backtest date to avoid having look-ahead bias in the analysis. The backtest functionality is available to clients who subscribe to one of FactSet s quantitative applications in the workstation, such as Alpha Testing and Portfolio Simulation.. 1. Screening Language In order to facilitate efficient access to a data item as of single time period for a universe of securities, FactSet offers an optimized cross-sectional data access method with the Screening Language. Given a data item, for example EPS, and a time period, for example Q4 2010, data for every entity in the specified universe can be fetched using the Screening Language. By default, the Screening Language does not allow iteration and therefore cannot be used to return a time series of data with a single request code. To request data as of a single historical date, a date must be specified as an absolute or relative date. Note: Many formulas in the Screening Language are current only. If an option for a date argument is not available when selecting a formula, this means that the formula does not accept a date reference Screening Date Format - Absolute Dates Absolute dates indicate a specific day, month-end, fiscal quarter-end, calendar quarterend, fiscal year-end, or calendar year-end as depicted in the examples below: A day: MM/DD/YYYY (e.g. 7/11/1999) Note: DD/MM/YYYY is not a valid date format A month-end: MM/YYYY (e.g. 6/1999) A fiscal quarter-end: YY/FQ or YYYY/FQ (e.g. 1999/1F, 2000/3F, 2001/2F) A calendar quarter-end: YY/CQ or YYYY/CQ (e.g. 1999/1C, 00/3C, 2001/1C) A fiscal year-end: YY or YYYY (e.g. 2000, 01, 1999) 1 P a g e U p d a t e d J une

2 1.2. Screening Date Format - Relative Dates Relative dates represent a date relative to the most recently updated period. For example, 0 (zero) represents the most recently updated period; -1 represents the time period prior to the most recently updated. The zero date is determined by the default time period or the natural frequency of the data being requested. Zero (0) when used with monthly data indicates the most recent month end. Negative one (-1) when used with annual data indicates one fiscal year prior to the most recently updated fiscal year. List of Relative Date Arguments: D WE W AM M AQ Q CQ AY Y CY 0D is the most recent trading day, -1D is one trading day prior. 0WE is the most recent trading week end, -1AW is the one actual week (7 days) prior to the most recent. 0W is the last day of the most recent trading week (usually Friday), -1W is the last trading day of the prior week. 0AM is the most recent trading day, -1AM is the same day, one actual month ago. 0M is the last trading day of the most recent month, -1M is the last trading day of the prior month. 0AQ is the most recent trading day, -1AQ is the same day 3 months prior 0Q is the last trading day of the company s most recent fiscal quarter, -1Q is the last day of the prior fiscal quarter. 0CQ is the last trading day of the most recent calendar quarter (March, June, September, or December), -1CQ is the last trading day of the prior calendar quarter. 0AY is the most recent trading day, -1AY is one actual year (365 days) prior 0Y is the last trading day of the company s most recent fiscal year, -1Y is the last trading day of the prior fiscal year. 0CY is the last trading day of the most recent calendar year (the last trading day in December), -1CY is the last trading day of the prior calendar year. For databases available on FactSet, there are a set of items that represent the piece of information on the database, such as sales, EPS and market value. Formulas that begin 2 P a g e U p d a t e d J une

3 with FG_ are FactSet Global formulas and are some of the most commonly used formulas to retrieve prices, estimates, valuation, growth, and fundamentals. The formulas return data from multiple database sources, based on a client's FactSet subscription. While the source can be different depending on the selected company, all formulas for a given company are pulled from the same database source. In database specific codes, the database is specified in the Screening code, such as in P_PRICE where the P_ element of the code denotes the pricing database and FF_SALES denotes the FactSet Fundamentals database with the FF_ element of the code. This distinction is highlighted in more detail throughout the examples below. 2. FF_ExtractDataSnapshot in MATLAB In MATLAB, the syntax for the FF_ExtractDataSnapshot function is: data = FF_ExtractDataSnapshot(factset, 'ids', 'item', { 'param,value'} ); Note: In the syntax diagram, the braces indicate optional FactSet code arguments, not MATLAB cell arrays. where, data The name of the data structure to create, i.e. titled data or x. factset ids Item(s) Name of the FactSet fetch channel. CellString array with a list of one or more security identifiers. CellString array with a list of one or more FactSet data items in the Screening language. optional arguments, backtestdate currency cal The backtestdate as of which the data is retrieved. If no date is specified, a backtest date will not be set. The date can be entered using a relative date or absolute date. The currency in which the data is to be returned, using a string with the three character ISO code (e.g. USD or EUR ). Calendar setting, arguments include: 3 P a g e U p d a t e d J une

4 FIVEDAY: Displays Monday through Friday, regardless of whether there were trading holidays. FIVEDAYEOM: Displays Monday through Friday including a weekend date if it falls on the last day of the month. Where the month-end does not fall on a weekend, the calendar will act just as the standard five-day calendar. SEVENDAY: Displays Monday through Sunday. AAM: For Exchange code uses the calendar of a specific exchange, represented by the exchange code. If there is no calendar available for a specific exchange, the calendar will default to FIVEDAY. Note: The calendar setting does not get applied to the default date output field when using ExtractDataSnapshot. To display a corresponding date to the extracted value(s), with calendar settings applied, a date code must be added as an item in the request syntax. universe universegroup Screening expression to limit the universe Specifies what mode of screening to use. The default screening mode is Equity. For Fund screening and Debt screening the universegroup argument has to be used with either FUND or DEBT respectively. 4 P a g e U p d a t e d J une

5 Example 1: This example is using the standard Screening syntax to retrieve the quarterly sales value from the FactSet Fundamentals database for IBM using the Screening code FF_SALES(QTR, ). >> data = FF_ExtractDataSnapshot(factset,'ibm','ff_sales(QTR, )'); Entities: 1 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 1 Item (3): Type: Double Desc: ff_sales (Sales) data = Id: 'ibm' Date: ff_sales: Note: See Table 1 in Appendix for the Screening syntax for the top 25 most frequently used data items from the FactSet Fundamentals database. Example 2: This example is using the standard Screening syntax to retrieve the quarterly sales values in USD from the FactSet Fundamentals database for Exxon Mobile and Statoil using the Screening code FF_SALES(QTR, ). >> data = FF_ExtractDataSnapshot(factset,'xom,stlno','ff_sales(QTR, ,,USD)'); Entities: 2 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 2 Item (3): Type: Double Desc: ff_sales (Sales) 5 P a g e U p d a t e d J une

6 Note: All Screening codes used in the item parameter have their arguments in different positions depending on the source of the code. For example, the currency argument for the price code from the pricing database using P_PRICE has it in the 2ND position P_PRICE(-5D,USD), while the sales code from FactSet Fundamentals using the code FF_SALES(QTR,-1,RP,USD) has it in the 4th position. >> data.ff_sales Example 3: In this example, instead of specifying securities in the ids field, as was done in examples 1 and 2 above, an index universe is specified and the items codes, such as price or sales are extracted for all of the constituents of for example the S&P 500. The syntax to extract the price from the IDC/Exshare database using the code P_PRICE( ) and sales from the FactSet Fundamentals database using the code FF_SALES(QTR, ) for the current constituents of the S&P 500 using the code ISON_SP500 is the following: >> data = FF_ExtractDataSnapshot(factset,'','ff_sales(QTR, ),p_price( )', 'ison','sp500'); The universe is specified at the end of the code with the ison & sp500 arguments, which are broken down from the actual Screening syntax that would be used in an Excel template is ISON_SP500. In the output with this code, the ID field brings back the CUSIPs of the companies in the S&P 500. >> data Entities: 500 Items: 4 Dates: 1 Layout: EIT Orientation: None Rows: 500 Item (3): Type: Double Desc: ff_sales (Sales) Item (4): Type: Double Desc: p_price (Price - Close or Current Intraday) data = 6 P a g e U p d a t e d J une

7 1x500 struct array with fields: Example 4: In this example, retrieve the latest quarterly sales with the FactSet Fundamentals code FF_SALES in local currency for the specified universe as the constituents of the MSCI EAFE index. The Screening code for this universe is ISON_MSCI_EAFE(0,1). In the output, the ID field brings back the CUSIPs of the companies in the index. >> data= FF_ExtractDataSnapshot(factset,'','ff_sales(QTR,0)','ison','msci_eafe','isonParams ','0,1'); Entities: 911 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 911 Item (3): Type: Double Desc: ff_sales (Sales) Note: The isonparams portion of the code is used when specifying an index, as demonstrated in this example and in Examples 5 and 6. Further details of the ISON function options for the Universe specification are in Online Assistant page Example 5: In this example, extract the latest closing price for the specified universe as the constituents of the MSCI USA index, using the pricing database code P_PRICE. The Screening code for this Universe is ISON_MSCI_COUNTRY(984000,0,CLOSE,OFF). In the output, the ID field brings back the CUSIPs of the companies in the index. >> data= FF_ExtractDataSnapshot(factset,'','p_price(0)','ison','msci_country','isonParams',' '); Entities: 603 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 603 Item (2): Type: Date Desc: Date Item (3): Type: Double Desc: p_price 7 P a g e U p d a t e d J une

8 Example 6: In this example, extract the latest annual EPS ratio for the specified universe as the constituents of the Russell 1000 Index, using the FactSet Fundamentals code FF_EPS. The Screening code for this Universe is ISON_RUSSELL(1000,0). In the output, the ID field brings back the CUSIPs of the companies in the index. >> data= FF_ExtractDataSnapshot(factset,'','ff_eps(ANN,0)','ison','RUSSELL','isonParams',' 1000'); Entities: 1004 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 1004 Item (3): Type: Double Desc: ff_eps (Earnings Per Share - Fiscal Period) Example 7: In this example, extract the decile ranking of the S&P 500 companies based on the most recently reported quarterly earnings per share (EPS) using the FactSet Fundamentals formula FF_EPS. The FactSet UDECILE function returns the decile rank (1-10) of a company against a specified universe when both the company and the universe are evaluated for the same formula. The number 1 is the highest rank and is assigned to the companies which fall within the top decile of the specified universe, in this case the S&P 500. >> data = FF_ExtractDataSnapshot(factset,'','udecile(ison_sp500,ff_eps(QTR,0))', 'ison','sp500'); Entities: 500 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 500 Item (3): Type: Double Desc: udecile (Univ Decile Rank) The data.id and data.udecile arguments extract the CUSIP of the company and corresponding decile. 8 P a g e U p d a t e d J une

9 >> data.id M10 >> data.udecile For a comprehensive list of FactSet universe ranking functions that can be used with the Screening Language, that include RANK, DECILE, PERCENTILE, and QUARTILE see Online Assistant page Example 8: In this example utilize the backtest functionality to retrieve the latest quarterly sales value and the corresponding fiscal period end date for a list of securities lagged by 45 days. To retrieve sales the FactSet Fundamentals code is FF_SALES and for retrieving the Fiscal Period End date in MM/YYYY format the FactSet Fundamentals code is FF_FP_END_DATE. When using the lag argument (lag options: specified number of days, weeks, months, quarters, or years), FactSet retrieves data as it was known at the time of the rebalance date. For example, if returns are calculated for the universe rebalanced in December 1990, a custom P/E formula can be set up using the price in December 1990, then lag the date of the earnings (to the most-recently reported quarter at that point in time), for example, to September. By lagging EPS, it is possible to use the P/E that was known to the public in December A lag argument does not need to be added to pricing and shares formulas to avoid lookahead bias, because these are bits of information that would have been publicly known at the time of the backtest date. >> data = FF_ExtractDataSnapshot(factset,'ibm,hd,pg,fds,fit','FF_FP_END_DATE(QTR,0 L45D),FF_SALES(QTR,0 L45D)','backtestdate',' '); 9 P a g e U p d a t e d J une

10 Entities: 5 Items: 4 Dates: 1 Layout: EIT Orientation: None Rows: 5 Item (3): Type: String Desc: ff_fp_end_date (Fiscal Period End Date: MM/YYYY) Item (4): Type: Double Desc: ff_sales (Sales) >> data.ff_fp_end_date '09/2010' '10/2010' '09/2010' '11/2010' >> data.ff_sales P a g e

11 Alternatively, in order to retrieve the same data but with setting a relative date of -1D as the backtest date, the following syntax would be used. In this example a backtest date is set as of 2 trading days ago. >> data = FF_ExtractDataSnapshot(factset,'ibm,hd,pg','FF_FP_END_DATE(QTR,0 L45D),FF_SALES(QTR,0 L45D)','backtestdate','-1D'); Entities: 3 Items: 4 Dates: 1 Layout: EIT Orientation: None Rows: 3 Item (1): Type: Entity Desc: Id Item (2): Type: Date Desc: Date (Date: MM/DD/YY) Item (3): Type: String Desc: ff_fp_end_date (Fiscal Period End Date: MM/YYYY) Item (4): Type: Double Desc: ff_sales (Sales) >> data.ff_fp_end_date '09/2013' '10/2013' '09/2013' >> data.ff_sales P a g e

12 Example 9: In this example, extract valuation data for 2 bonds the name of the company issuing the bond with the code FI_NAME_ISS and the value of the bond with the code FTID_PRICE. The FI_NAME_ISS code retrieves along with the company name the coupon and maturity date of the bond. The data is retrieved using the bond identifiers 00077TAA for ABN Bank and 88579EAE for 3M. For more details regarding the FactSet Fixed Income Manager refer to Online Assistant page >> data = FF_ExtractDataSnapshot(factset,'88579EAE,00077TAA','FI_NAME_ISS(0),FTID_PR ICE(0)','universeGroup','DEBT'); Note: Fixed income securities need to use the universegroup, debt argument. Entities: 2 Items: 4 Dates: 1 Layout: EIT Orientation: None Rows: 2 Item (3): Type: String Desc: fi_name_iss (Name-Issue) Item (4): Type: String Desc: ftid_price (Price) >> data.id 88579EAE 00077TAA >> data.fi_name_iss '3M Co % 15-AUG-2013' 'ABN AMRO Bank NV (NY Branch) 7.75% 15-MAY-2023' 12 P a g e

13 Example 10: In this example, retrieve proprietary data stored uploaded into FactSet and stored in an Open FactSet Database (OFDB). OFDB is a high-performance multi-dimensional database system used to securely store proprietary numeric and textual data on FactSet. OFDB is ideal for users who manage large portfolios or maintain extensive historical proprietary databases. OFDB optimizes large, multi-dimensional databases, giving FactSet users highly flexible, factset access to large volumes of complex data that can be used in many different applications. OFDB is based upon Online Analytical Processing technology, which is the basis for multi-dimensional databases. Retrieve the latest closing price using P_PRICE for the constituents of an OFDB, titled in this example 5002_EAGLE. To test this example, reference an actual OFDB file that is stored. >> data = FF_ExtractDataSnapshot(factset, '','P_PRICE(0D)','ofdb','5002_EAGLE'); Note: When using the ofdb parameter, the retrieved constituents are current only. In order to extract a more dynamic universe of constituents from an OFDB as of a specific date, an ofdbdate argument must be used. The alternative request would thus be set up as: >> data = FF_ExtractDataSnapshot(factset, '','P_PRICE(0D)','ofdb','5002_EAGLE', 'ofdbdate',' '); Example 11: In this example, extract the price for the universe of 5 comparable companies to IBM using the Universe argument to returns the companies that pass given screening parameters. The Universe argument is combined in this example with the COMPARE_ function, which generates a list of comparable companies for a specified target company using a specific database. Depending on which COMPARE database is used, the corresponding database grouping and comparison formulas must be used as well. For example, if you choose COMPARE_FF_ADRS, you must use the FactSet Fundamentals-specific grouping and comparison formulas. For a comprehensive list of database specific COMPARE functions, refer to Online Assistant page P a g e

14 The 5 comparable companies to IBM in this example are from the FactSet Fundamentals database (excluding ADRs), in IBM's FactSet Industry, screened by net income, using the FactSet Fundamentals database code FF_NET_INC. >> data = FF_ExtractDataSnapshot(factset,'','P_PRICE', 'UNIVERSE','COMPARE_FF_NOADRS(IBM,PUBLIC:F_FACTSET_INDUS_N,PUBLI C:FF_NET_INC(ANN,0),5)'); Entities: 5 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 5 Item (3): Type: Double Desc: p_price (Price - Close or Current Intraday) >> data.id P a g e

15 Example 12: In this example, the PMW function is used to return portfolio-specific information from valid Portfolio Analysis portfolios (e.g., OFDB, CSTM, ACCT, PRT, and Benchmark files). These functions are similar to OFDB functions, which can also be used to return information from OFDB databases, but are tailored for use with holdings databases used in Portfolio Analysis. PMWU PMWDB PMWAT PMWSM Returns a universe of companies from a given portfolio. Returns data from a specified column/field within a given portfolio. Returns asset type and asset classification data for a given portfolio. Returns data from the security master file. By default, PMW* functions return split-adjusted data. They are available in Screening syntax only and cannot be used with FQL. For further details on the PMW function refer to Online Assistant page Note: A SHARES field is required within the specified database in order to return data using PMW* functions. Since Portfolio Analysis is largely driven by the share positions supplied in holdings databases, PMW* functions also require a SHARES field to more closely replicate application behavior. To access data from holdings databases using the PMW* codes, it is necessary to first add the portfolio in Portfolio List Manager. >> data = FF_ExtractDataSnapshot(factset,'','PMWDB(#p1,shares,0),PMWAT(#p1,0)','p1','CLI ENT:SCCOMP.CSTM','universe','PMWU(#p1,0)=1'); Note: It is necessary to specify within the syntax, the portfolio file (e.g., OFDB, CSTM, ACCT, PRT, and Benchmark files) as a global variable, denoted in the syntax example above as p1. 15 P a g e

16 Example 13: In this example, using the SUM function, return the 20-quarter sum of price-to-sales per share for BNP Paribas, beginning with the latest fully-reported quarter. >> data = FF_ExtractDataSnapshot(factset,'BNP-FR','SUM20(ff_psales(QTR,0))'); >> data Entities: 1 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 1 Item (3): Type: Double Desc: sum20 data = Id: 'BNP-FR' Date: sum20: Example 14: In this example, for the securities BNP and Alcatel-Lucent, add the latest annual operating income to the general industry classification output flag. If that flag output is a float value equal to 4, will add the operating income to one, if not, add operating income to zero. In this example demonstrating the use of addition, however, subtraction, division and multiplication can be performed as well. >> data = FF_ExtractDataSnapshot(factset,'BNP-FR,ALU- FR','FF_OPER_INC(ANN,0,RF)+IF(FLOAT(FF_GEN_IND)=4,1,0)'); Entities: 2 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 2 Item (3): Type: Double Desc: ff_oper_inc (Operating Inc Before Unusual Items) 16 P a g e U p d a t e d J u n e

17 Example 15: In this example, for the securities 3M and Conoco Phillips, extract the Permanent Security ID (as defined by the Factset Symbology database). >> data = FF_ExtractDataSnapshot('factset','mmm,cop','fs_perm_sec_id('''')'); Entities: 2 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 2 Item (3): Type: String Desc: fs_perm_sec_id (Permanent Security ID From 'X' ID) data = 1x2 struct array with fields: Id Date fs_perm_sec_id >> data.fs_perm_sec_id 'R17LLM-S-US' 'L6CX6R-S-US' Alternatively, for the same securities the following syntax would be used to retrieve the corresponding CUSIP. And to do that, the dataitemname= and heading= paramaters must be used. >> data = FF_ExtractDataSnapshot('factset','mmm,cop','(cusip)','dates',' ','heading', ',,cusip','dataitemname',',,cusip'); Entities: 2 Items: 3 Dates: 1 Layout: EIT Orientation: None Rows: 2 Item (3): Type: String Desc: cusip (Company Cusip) 17 P a g e U p d a t e d J u n e

18 >> data data = 1x2 struct array with fields: Id Date cusip >> data.cusip '88579Y10' '20825C10' Example 16: In this example fund screening is used to limit the universe and extract name and price for the funds passing the screening criteria. >> data = FF_ExtractDataSnapshot(factset,'','SPAR_MEUR_CO_NAME,SPAR_MEUR_CLOS E_PRICE(0)','universe','SPAR_MEUR_COUNTRY=PROPER(''FINLAND'')','universe Group','fund','backtestdate','3/26/14') 18 P a g e U p d a t e d J u n e

19 Appendix Table 1: Top 25 most commonly used FactSet Fundamentals formulas The table lists the top 25 most commonly used FactSet Fundamentals formulas, displaying the arguments for retrieving the data as of the latest available value denoted with the 0 date argument. That can be substituted with actual dates or other relative dates. Description Acquisition of Business (Cash Flow) Capital Expenditures (Fixed Assets) Capital Expenditures (Other Assets) Cash Dividends Paid Cash Flow from Financing Activity - Net (Cash Flow) Cash Flow from Investing Activity - Net (Cash Flow) Cash Flow from Operating Activity - Net (Cash Flow) Changes in Working Capital Common Equity (Total) Cost of Goods Sold Excluding Depreciation & Amortization Depreciation & Amortization (Cash Flow) Extraordinary Items (Cash Flow) Funds from Operations Issuance of LT Debt Long Term Debt excluding Capital Lease Obligations Minority Interest - Accumulated Preferred Stock - Carrying Value Price - Close for Calendar Period End Purchase of Investments Reduction of LT Debt Repurchase of Common & Pref Stock Sale of Common & Pref Stock Sales of Fixed Assets & Businesses Sales or Revenues - Net FF_ExtractDataSnapshot Syntax FF_ACQ_BUS_CF(QTR,0) FF_CAPEX_FIX(ANN,0) FF_CAPEX_OTH(ANN,0) FF_DIV_CF(ANN,0) FF_FIN_CF(ANN,0) FF_INVEST_CF(ANN,0) FF_FUNDS_OPER_GROSS(ANN,0) FF_WKCAP_CHG(ANN,0) FF_COM_EQ(QTR,0) FF_COGS_XDEP(ANN,0) FF_DEP_EXP_CF(ANN,0) FF_XORD_CF(ANN,0) FF_FUNDS_OPER_GROSS(ANN,0) FF_DEBT_LT_ISS_CF(ANN,0) FF_DEBT_LT_XCAP(ANN,0) FF_MIN_INT_ACCUM(ANN,0) FF_PFD_STK(QTR,0) FF_PRICE_CLOSE_CP(ANN,0) FF_INVEST_PURCH_CF(ANN,0) FF_DEBT_LT_REDUCT_CF(ANN,0) FF_STK_PURCH_CF(ANN,0) FF_STK_SALE_CF(ANN,0) FF_SALE_ASSETS_BUS_CF(ANN,0) FF_SALES(ANN,0) 19 P a g e U p d a t e d J u n e

20 Short-Term Debt (incl. Current Portion of LTD) FF_DEBT_ST(ANN,0) 20 P a g e U p d a t e d J u n e