WRDS SEC Analytics Suite - Pennsylvania State · PDF file•WRDS SEC Analytics Suite ......

10/22/2011

New Products and Research Appl icat ions

Denys Glushkov, Rabih Moussawi and Luis Palacios

WRDS SEC Analytics Suite

Today’s Session

Over the next 45 minutes

• Research Applications & Macros

• WRDS SEC Analytics Suite

• New TAQ Datasets that makes research

easy

• Capital IQ Database. Point-in-time. More

US Coverage. More Variables. Global.

• Analyst Data.

• International data. Factset.

Wharton Research Data Services 3 10/22/2011

New Research Tools:

Research Applications & Macros

Wharton Research Data Services 4

New Research Tools at WRDS

Research Applications: Example for Fama-French Factors

10/22/2011 Wharton Research Data Services 5


Fama-French Factors. Replication. Comparison.



Research Applications: Example for „Return Gap‟



SAS Macros


… Macros are Easy to Invoke. One Line.

%ICLINK (IBESID=IBES.ID,CRSPID=CRSP.STOCKNAMES,OUTSET=WORK.ICLINK); %CRSPMERGE(S=, START=, END=, SFVARS=, SEVARS=, FILTERS=, OUTSET=); %EVTSTUDY(INSET=,OUTSET=,ID=,EVTDATE=,ESTPER=,START=,END=,GAP=,GROUP=,MODEL=);


…Macros are Documented. Not Black Boxes.


…More Research Tools and Documentation


• Sample Codes

• SAS Notes

• Research Guides

• Data Overviews

Where all these Tools are located?


WRDS SEC Analytics Suite


Introducing the WRDS SEC Analytics Suite Centralized storage & parsing of SEC filing contents

• More than 11 million records of electronic filings with the

SEC since 1994.

• Over 3.6 million text and HTML files available on the

WRDS server for all 10-K, 10-Q, 8-K, Proxy filings, 13D/G

and 13F reports since 1994

• Datasets for over 2 million 8-K events/items and 7 million

filing exhibits

• Link data together with the help of the historical GVKEY,

CUSIP and CIK link tables

• Easy access to pre-parsed data including confirmed

period of report, time of filings, historical state of

incorporation and more


Records of all electronic filings on EDGAR SEC filings continue to grow every year


11,335,071 filings in SEC‟s EDGAR

since 1994 and until October 21, 2011

Updated everyday at 6am

Insider filings on EDGAR (41%):

- Forms 3, 4, and 5

- SOX new rules on August 27, 2002

- Electronic filing on June 30, 2003

All 11+ Million Filings Records:

Identify Who filed What and When


Example of the available and ready-to-use parsed content

Going Private Transactions

• Extract the list of all Going

Private transactions that used

Form SC 13E3

• SC 13E3: reduce the number of

shareholders to fewer than 300 to

stop filing reports with the SEC

Use Web Query conditional statement

Form = SC 13E3

Use SAS Code: data SC13E3;

set sec.forms;

where form like 'SC 13E3%';

• Output: 9,446 filings for 1,977

distinct companies since 1994


Definition:

CIK is the company identifier,

FORM is the form type,

FDATE is the filing date, and

FNAME is the filing reference name

Yesterday‟s Insider Filings

• Corporate Insiders are the company‟s officers (executives), directors, and any beneficial owners of more than 10% of any class of equity stock.

• Forms 3, 4, and 5 are used to report ALL stock and option transactions by corporate insiders within two business days:

Form 3 is for initial filing.

Form 4 is for all transactions or changes in ownership.

Form 5 is for the annual statement of change in ownership.

• On June 30, 2003, electronic submission of insiders‟ filings was mandated

• On October 21, 2011, 585 insider filings were reported to the SEC


3 4 5

# of Filings 68 515 2

# of Companies 64 401 2

Proxy Contests

Notation of Proxy Reports: e.g. DEF 14A, PREM14A, DEFC14A, DEFS14A, etc. • Suffix: 14A vs. 14C

Schedule “14A” is for proxy materials

Schedule “14C” contains information statement

• Prefixes: PRE/DEF prefix denotes whether the filing is Preliminary or Definitive, then • Empty space is used between Prefix and Suffix for regular proxy materials. Otherwise:

M is used for proxy materials relating to a merger or acquisition

C prefix is for reports in connection with contested solicitation

N prefix denotes proxy materials when filed by non-management

S prefix is used in proxy materials for special meetings

R is used for revised proxy materials


Replicate the proxy fight sample in Fos (2011): The

Disciplinary Effects of Proxy Contests.

Use WRDS SEC to get the complete set of companies

that faced proxy contests (fights) since 1994.

Compare WRDS SEC proxy fights sample (left) with Fos

(2011) Figure 1.

Fos (2011): The Disciplinary Effects of Proxy Contests – Fig 1


Tender Offers

• Get the list of all tender offer related filings for all companies that faced

tender offers since 1994

• Schedule TO corresponds to Form SC TO: o Form SC TO-I: Tender offer statement by Issuer

o Form SC TO-T: Tender offer statement by Third Party

o Form SC TO-C - Written communication relating to an issuer or third party

• Number of Tender Offer Filings with the SEC since 1994: 39,548


as of 08/31/2011 SC TO-I SC TO-T SC TO-C

Original Filings 4,915 3,555 5,625

Amendments 8,863 16,590

Total 13,778 20,145

SEC Filings on WRDS

Explore the different types of SEC filings

• Filings archive updated weekly. Accessible by SAS, Perl or

Python, and stored in /wrds/sec/archives/

o 10-K and 10-Q: Annual and interim reports

o 8-K: Current reports

o DEF 14A and PRE 14A: definitive and preliminary proxy

statements

o 13F, 13D, and 13G: Institutional and beneficial ownership

reports

o UPLOAD and CORRESP: Comment letters from SEC staff

o CT ORDER: Confidential treatment orders

• SAS datasets in /wrds/sec/sasdata/ with parsed contents:

o Filing size, fiscal year end

o Date and Time Report of SEC Acceptance (Available after

May 2002)

o Confirmed Period of Report including Fiscal Period End

for 10-K and 10-Q, Event Date for 8-K, and Meeting Date

for proxy filings

o Historical state of incorporation and headquarters

o Historical as-reported SIC code


SEC Filings Archive in WRDS SEC Platform


Filing

Year

10-K Filings 10-Q

Filings

8-K Filings Proxy

Filings

13D

Filings

13G

Filings

13F

Filings

CT

Order

SEC Comment

Letters

All /A All /A All /A All /A All /A All /A All /A SEC Filers

1994 2,657 24% 7,592 8% 4,202 9% 3,742 17% 2,339 71% 8,580 61% 220 4% 0 0 0

1995 4,780 25% 17,753 11% 7,164 11% 6,283 9% 5,409 74% 13,949 66% 282 13% 0 0 0

1996 10,793 22% 36,099 9% 18,000 12% 11,462 10% 12,318 63% 20,536 67% 265 9% 0 0 0

1997 18,034 20% 41,475 7% 27,490 11% 15,673 8% 18,615 59% 38,541 54% 284 14% 0 0 0

1998 17,932 18% 41,697 7% 31,436 10% 15,564 8% 17,727 62% 47,438 53% 369 14% 0 0 0

1999 17,852 17% 42,582 8% 31,348 9% 15,400 8% 16,614 62% 44,145 58% 7,035 8% 0 0 0

2000 18,717 15% 47,101 7% 33,116 9% 16,543 11% 16,523 62% 44,135 56% 10,282 8% 0 0 0

2001 18,882 16% 45,175 7% 38,948 7% 15,764 12% 15,409 64% 42,322 57% 11,277 9% 0 0 0

2002 18,415 17% 42,929 8% 48,759 7% 14,957 12% 15,217 65% 39,333 66% 11,508 10% 0 0 0

2003 17,426 18% 39,289 8% 71,556 5% 14,312 14% 15,506 65% 38,504 65% 11,939 10% 0 0 1

2004 17,455 18% 38,404 8% 95,680 4% 15,069 19% 15,179 67% 39,609 62% 12,732 11% 0 633 874

2005 18,707 19% 39,224 10% 121,918 5% 15,730 19% 14,969 66% 42,956 58% 13,730 9% 0 8,728 8610

2006 17,657 17% 38,629 9% 111,438 4% 18,087 28% 16,011 65% 48,567 59% 15,154 10% 0 13,160 11424

2007 16,958 15% 37,649 7% 105,896 4% 18,232 32% 16,837 67% 53,501 60% 16,597 9% 0 12,129 11003

2008 16,953 18% 36,523 6% 94,530 4% 16,328 28% 15,709 69% 55,881 60% 18,542 10% 1,097 12,858 9798

2009 14,628 17% 33,545 7% 85,182 4% 17,348 30% 13,670 72% 50,558 67% 17,661 7% 1,494 14,712 12991

2010 13,295 17% 31,775 7% 83,485 4% 15,188 33% 12,936 70% 44,062 66% 17,802 7% 1,592 15,017 13779

2011 8,410 8% 3,729 16% 24,267 4% 5,606 30% 4,035 67% 34,141 71% 5,223 8% 394 1,392 1200

Total 269,551 621,170 1,034,415 251,288 951,781 170,902 4,577 78,629 69,680

Parsing Poison Pill Data using WRDS Query


Keep in the output

companies with no

matches (ie. no

poison pills)

Enter up to

5 strings to

match in

filings

contents

Test first with

one month or

subset of

companies

Choose forms

to use in

parsing

exercise

Matched Text

Selection Output

Parsing Poison Pill Output


Live Link to Actual Filing Line # Matches Meeting Date

Flexible Query Options


Example: Microsoft Corp recent 10-K


7,407,190 Exhibits

since 1994

http://www.sec.gov/Archives/edgar/data/789019/0001193125-10-171791-index.htm



http://www.sec.gov/Archives/edgar/data/826083/000095013407007558/0000950134-07-007558-index.htm


Exhibits Data

• All exhibits that are filed as separate documents in 10-K, 10-K, 8-K, and proxies

• Info about exhibit number, type, description, and exhibit filename • More than 1.74 million filings with > 7.4 million exhibits


0%

20%

40%

60%

10-K 10-K/A 10-KSB &/A 10-K405 &/A NT 10-K

10-K Types (for 10-K filers with GVKEY)

• <picture from parsed exhibits>



http://www.sec.gov/Archives/edgar/data/826083/0000950134-03-006596-index.html


Examples of Filing Exhibits

Ex. 21 – List of Subsidiaries: Proxy for Special

Purpose Vehicles following Feng, Gramlich, and

Gupta (2009, AR forthcoming)

Ex. 13 – ARS; Ex. 3 – Charter& Bylaws; Ex. 23 –

Consents; Ex. 31,32 – Certifications, Legal

Opinions, etc.

Ex. 10 – Material Contracts and Agreements: the

nature of the contract, whether the firm has

requested confidential treatment, and the filing

in which the material contract was disclosed.

SEC requires each firm to maintain an exhibit

list of all unexpired material coNtracts That The

Firm Has Entered Into In The Past Year (Item

14 Of 10-K)

Ex. 99 – Additional Exhibits Not Specifically

Indicated By Another Number

Ex. 101 – Attached Documents For Submitted

XBRL Information

SAS: TYPE Like '%-101%‘;


Filing time information in WRDS SEC platform


Intraday Returns around Late Filing Announcements

• Shows how fast are investors reacting to late 10-K filings announcements

• Companies have to disclose their inability to file the report timely and the reason for the delay, for 10-K

and 10-Q filings: typically a bad news.

• Form 12b-25 generates a NT10-K or NT10-Q late filing reports. Late filing notices should be filed within

one business day of the due date

o Keep NT10-K NT10-Q reports between 10:30 a.m. and 3:00 p.m.

o Compute 30mn intraday returns using TAQ trades

o Line-up all the intraday returns before and after filing time


Average 30-minute Interval Returns

Time period ALL 2003 2004 2005 2006 2007 2008 2009 2010

[-60,-31]mn 0.11% 0.62% 0.25% 0.00% -0.10% 0.05% -0.58% 0.65% 0.55%

[-30,-1]mn -0.02% 0.17% -0.36% -0.08% -0.14% 0.25% -0.10% -0.12% -0.37%

Filing Time -0.09% -0.32% 0.18% -0.10% -0.30% -0.37% 0.03% -1.01% 0.32%

[31,60]mn -0.03% -0.21% -0.26% -0.05% -0.15% -0.13% -0.22% 0.95% -0.22%

[61,90]mn 0.08% 0.50% -0.43% -0.13% -0.04% -0.22% 0.07% 0.25% 0.44%

[91,120]mn 0.10% 0.02% 0.48% 0.04% 0.19% 0.09% -0.09% 0.52% 0.14%

8-K Items: notify shareholders and the SEC of material information or major

unscheduled events -- Example: Valeant Pharma‟s 8-K


New 8-K Item

starting in

March 2010

2,016,879 Corporate

Events that triggered

8-K filings since 1994

Time of Filing or SEC

Acceptance Time

http://sec.gov/Archives/edgar/data/885590/0000950123-10-090858-index.htm



8-K Items after August 23, 2004


8-K Item # Form 8-K Item Description Records %

1.01 Entry into a Material Definitive Agreement 132,718 9.50%

1.02 Termination of a Material Definitive Agreement 11,883 0.85%

1.03 Bankruptcy or Receivership 2,000 0.14%

2.01 Completion of Acquisition or Disposition of Assets 21,921 1.57%

2.02 Results of Operations and Financial Condition 154,787 11.07%

2.03 Creation of Off-Balance Sheet Arrangement 33,496 2.40%

2.04 Accelerating Financial Obligation or Off-Balance Sheet 2,730 0.20%

2.05 Cost Associated with Exit or Disposal Activities 4,210 0.30%

2.06 Material Impairments 2,511 0.18%

3.01 Delisting 9,083 0.65%

3.02 Unregistered Sales of Equity Securities 29,029 2.08%

3.03 Material Modifications to Rights of Security Holders 7,042 0.50%

4.01 Changes in Registrant's Certifying Accountant 15,693 1.12%

4.02 Non-Reliance or a Related Audit Report 5,578 0.40%

5.01 Changes in Control of Registrant 6,513 0.47%

5.02 Departure of Directors or Certain Officers 116,949 8.37%

5.03 Amendments to Articles of Incorporation or Bylaws 21,609 1.55%

5.04 Temporary Suspension of Trading 820 0.06%

5.05 Amendments to the Registrant's Code of Ethics 1,285 0.09%

5.06 Change in Shell Company Status 1,524 0.11%

5.07 Submission of Matters to a Vote of Security Holders 9,912 0.71%

6.01 ABS Informational and Computational Material 148 0.01%

6.02 Change of Servicer or Trustee 504 0.04%

6.03 Change in Credit Enhancement or Other External Support 35 0.00%

6.04 Failure to Make a Required Distribution 39 0.00%

6.05 Securities Act Updating Disclosure 49 0.00%

7.01 Regulation FD Disclosure 99,257 7.10%

8.01 Other Events 190,233 13.61%

9.01 Financial Statements and Exhibits 516,149 36.93%

Total 1,397,707

M&A

8-K Items before August 23, 2004


8-K Item # Form 8-K Item Description Number of

Records % of 8-K Records

1 Changes in control of registrant 18,733 3.11%

2 Acquisition or disposition of assets 36,023 5.98%

3 Bankruptcy or receivership 3,326 0.55%

4 Changes in registrant's certifying accountant 17,862 2.96%

5 Other events 212,403 35.26%

6 Resignations of registrant's directors 2,931 0.49%

7 Financial statements and exhibits 247,502 41.08%

8 Change in fiscal year 1,942 0.32%

9 Regulation FD Disclosure 37,270 6.19%

10 Amendments to the Registrant's Code of Ethics 82 0.01%

11 Temporary Suspension of Trading 209 0.03%

12 Results of Operations and Financial Condition 24,188 4.01%

13 Receipt of an Attorney's Written Notice 5 0.00%

Total 602,476

Advanced Access using WRDS Server

• Take advantage of local storage of filings and

index datasets with PC-SAS or UNIX-SAS

• Use PERL or SAS regular expression

capabilities to parse thousands of filings and

build custom-tailored data sets in one step

• WRDS Research Macros are standardized

and well-documented SAS programs that can

be modified and invoked in one line

• Effective, transparent and extensible SAS

codes, including:

o LineParse: Line-by-Line parser that

preserves tabular format.

o TextParse: Parses out the match line

& a pre-specified number of preceding

characters.

o ParaParse: Extracts a paragraph with

pre-specified number of lines around a

string.


„Fraud‟ or „Irregularities‟ Related Bankruptcies /* Macro Example: Parse Bankruptcy Related 8-K’s – Total of 5,277 Filings */ data parse_input; /* 1. Use WFORMS, WFORMS2, EXHIBITS, ITEMS8K, or ITEMS8K2 as inputs */ set SEC.ITEMS8K2; /* 2. Define Your Sample: All bankruptcies */ where NITEM in ('3','1.03') and FSIZE>0; /* 3. Create a Variable with Physical Filing Link */ FNAME2 = cats("/wrds/sec/archives/",FNAME); run; /* 4. Define Match Strings, Tags, or Patterns */ %let string = fraud|irregularities; /* 5. Execute Macro */ %lineparse(inset=parse_input,outset=parse_output,fname_full=fname2,tstr=&string);


Introducing CIK link tables

• CIK link tables are datasets that map CIK to all historical company legal

names, CUSIP numbers, and other identification information

o WCIKLINK_NAMES lists of all company names for a given CIK

o WCIKLINK_CUSIP maps a CIK to all CUSIPs that appear in a

company‟s filings

o WCIKLINK_GVKEY maps between GVKEY and „Historical‟ CIKs

• Helps retain historical records for companies that are undergoing

restructuring and who are more likely to change their CIK filing number

o Essential tool for when you want to track all historical filings for public

companies

o Researchers use GVKEY-CIK historical maps to avoid selection and

survivorship bias concerns


Example: K-Mart Historical GVKEY-CIK Map


Expediting Microstructure Research


New TAQ Datasets

• Provide Daily TAQ feed with Millisecond timestamps

• Quote datasets are growing exponentially in size due to algorithmic trading and continuous changes to the prevailing quote.

o 1 year of data in 1993: 11GB

o 1 year of data in 2010: 9,475GB (851 X)

• WRDS decided to generate New Datasets of the following:

o NBBO Quotes at the end of each second for all stocks

o Merged Trades/Quotes Datasets: for each trade add the prevailing NBBO quote information at second -5, -2, -1, and 0, relative to the trade time

• WRDS will provide the SAS codes for:

o NBBO Quote generation macro

o Lee and Ready (1991) algorithm

o Daily Buy/Sell Imbalances

o Matching TAQ Symbol to CRSP Permno


NBBO Research Application • Regulation NMS – National Market System: calculate National Inside Quote from valid

quotes across various exchanges: Best Bid (BB), Best Offer (BO), Size at BB, Size at BO

• Quote Rule: http://www.sec.gov/answers/trdexbd.htm o best price at which a market maker is willing to trade

o a prevailing quote of an exchange is the most recent valid quote from that

exchange

o every new quote by an exchange supersedes its previous prevailing quote

• NBBO calculation every second because of TAQ Monthly feed time stamp granularity

• Evaluation of accuracy of WRDS NBBO algorithm:

o Minimize the percentage of locks and crosses within an NBBO

o Maximize the percentage of Inside Trades

• SAS Code: WRDS Research Applications

o Invocation: %nbbo (yyyymmdd=20080606, outset=myfile);

• Evaluation of execution speed of WRDS NBBO algorithm SAS Macro on WRDS server

o To create a 1998 NBBO daily dataset for all Stocks: 26 seconds

o To create a 2006 NBBO daily dataset for all Stocks: 9 minutes 37 seconds


http://www.sec.gov/answers/trdexbd.htm

NBBO Algorithm: SAS Code Logic


Exchange X

AskX BidX

Exchange Y

Exchange Z

National Inside Quote Best Bid Best Offer

BB=max(Bidi) BO=min(Offeri)

AskY BidY

AskZ BidZ

BEFORE Last step: Determine Eligible prevailing quotes for

NBBO using MODE quote condition and with sizes>0

Prevailing Quotes

Tim

e

Ask’X Bid’X

Lee and Ready Research Application • Use NBBO instead of the Exchange-Specific Quote, in the Quote Test

• Do not aggregate the trades within the same second: apply quote test and tick test to

individual trades independently.

• Have for each trade the quotes at the end of:

o -5 and -2 seconds: Lee and Ready (1991) original 5 second rule, or later findings

on -2 seconds delay

o -1 second: ie. choose the

prevailing quote at the

beginning of the second during which the trade

occurred.

o 0 second: ie. choose the quote at the end of the

second during which the

trade occurred.


In 1 second, for MSFT

- Share Volume: 599,266

- $ Volume: $16 million

Lee and Ready (1991)


/* Decide on Quote Lag: Lee and Ready (1991) use 5-Second Rule */

/* Select Period */

%let yymmdd=20090120;

/* Lee and Ready Algorithm */

data Lee_Ready;

set TAQ.WCT_&yymmdd;

where time between "09:30:00"t and "16:00:00"t

and price>0 and size>0;

/* Apply Quote Test first */

LeeReady=sign(Price-MidPoint1);

/* Then, Apply Tick Test */

if LeeReady=0 then LeeReady=TICK;

keep symbol date time price size LeeReady;

run;

Linking TAQ and CRSP Data

• Linking without a primary identifier: Define a primary identifier, first o “TICKER SYMBOL – VINTAGE DATE” as a primary identifier

o Use CUSIP as primary linking identifier then add ticker matches

o TCLINK.SAS Macro to create TCLINK link-table between TAQ Ticker Symbols and PERMNO

• Invoke TAQ-CRSP Linking Macro in one line within code: %tclink(BEGDATE=199301,ENDDATE=201012,OUTSET=home.tclink);

• Flag matches and provide link accuracy metrics

• Efficient Coding that highlight best practices and runs on the fly (automatic

updating and low maintenance cost)


Capital IQ - People Intelligence


People Intelligence on WRDS

• Compensation Data for over 46,000 global companies, with PIT collection since 1998:

o Summary Compensation: 51 summary variables + executive/director characteristics

1.92+ million records for 346K+ officers and directors in 46K+ distinct companies

95% of company-year records from: US(SEC- 56%), Canadian (SEDAR), Indian, UK, Australian, European, and Chinese (&HK) filings, based on currency information. 49% of companies incorporated in the US.

o Detailed Compensation: 46 stock/option grant level variables

1.27+ million obs. for 109K+ executives in 19K+ companies

Coverage: US, Canada, Australia, UK, Euro: 79% -- India, China and HK: 17%

• Professional Affiliation and Function Data 7.6 million functions for 4.6 million Company*Person relationships for 2.55 million

persons and 478K entities

47% with Private Companies, 22% with Public Companies, 18% with Educational Institutions, and 10% with Private Investment Companies and Public Funds

• Person Data:

Person directory and biography data for 2.67 million persons


Example: Goldman Sachs 2009 Proxy filed on 04/07/2010 http://www.sec.gov/Archives/edgar/data/886982/0001193125 -10-078005-index.htm


PIT aspect: filing date 20100407

Point-in-Time Nature

• Each Proxy filings provides compensation for 5 executives (highest paid /

top in corporate hierarchy): this year and last 2 years compensation

numbers

• In future filings, new executives will have 2 year of compensation history

(if any), and current executives will report again their previously reported

compensation numbers

• Research applications using Point-In-Time structure: o Examine restatements/changes in reported executive compensation

o Point-In-Time compensation data items before and after FAS 123R


Collected Summary Compensation Data


Var # Summary Compensation Type Var # Summary Compensation Type

1 Salary 27 Director Non-Equity Incentive Plan Compensation

2 Bonus 28 Director Change in Pension Plan 3 Other Annual Compensation 29 Director All Other Compensation 4 Restricted Stock Awards 30 As Reported Total Director Compensation

5 Stock Grants 32 Unexercised Unearned Options 6 Stock Options 33 Unexercised Unearned Options Value

7 Long Term Incentive Plan 36 Number of Shares Acquired on Vesting

8 All Other Compensation 37 Value Realized on Vesting 9 Exercised Options 38 Shares or Units Not Vested

10 Exercised Options Value 39 Shares or Units Not Vested Value 11 Exercisable Options 40 Unearned Shares or Units Not Vested

12 Exercisable Options Value 41 Unearned Shares or Units Not Vested Value 13 Unexercisable Options 44 Director Stock Grants 14 Unexercisable Options Value 45 Director Stock Options

21 Option Awards 46 Estimated Payments in Event of Termination Without Cause

22 Change in Pension Plan/Non-Qualified Deferred Comp Earnings

47 Estimated Payments in Event of Change in Control

23 As Reported Total Compensation 48 Non Equity Incentive Plan Compensation 24 Director Fee 49 Unclassified Options 25 Director Stock Awards 50 Unclassified Options Value

26 Director Option Awards 51 Director Bonus

Derived Compensation Data Items


Comp. Variable Components Comp. Variable Components

15. Total Annual Cash

Compensation

Salary 16. Total Short Term

Compensation

Salary

Bonus Bonus

Other Annual Compensation Other Annual Compensation

Director Fees

18. Total Calculated

Compensation

Salary

Director Non-Equity Incentive Plan Compensation Bonus

Non-Equity Incentive Plan Compensation Other Annual Compensation

Director Bonus Stock Awards

Non-Equity Annual Incentive Plan Stock Grants

Non-Equity Long Term Incentive Plan Long Term Incentive Plan (LTIP)

19. Total Value of Options

Exercised Options Value All Other Compensation

Exercisable Options Value Option Awards

Unexercisable Options Value Change in Pension Plan/Non-Qualified Deferred Comp Earnings

Unearned Unexercised Options Value

Unclassified Options Value Director Fees

Unexercised Options Value Director Stock Awards

20. Total Number of

Options

Exercised Options Director Option Awards

Exercisable Options Director Non-Equity Incentive Plan Compensation

Unexercisable Options Director Change in Pension Plan/Non-Qualified Deferred Comp Earnings Unearned Unexercised Options

Unclassified Options Director All Other Compensation

Unexercised Options Director Stock Grants

42. Total Value of Stock Awards

Value Realized on Vesting Non-Equity Incentive Plan Compensation

Shares or Units Not Vested Value Director Bonus

Unearned Shares or Units Not Vested Value Non-Equity Annual Incentive Plan

43. Total Number of Stock

Awards

Shares Acquired on Vesting Non-Equity Long Term Incentive Plan

Shares or Units Not Vested

Unearned Shares or Units Not Vested

FPE Year # of ALL CIQ Companies

# Comps excluding

subsidiaries

US filing companies or

subsid.

CA filing companies, or subsid.

Other Global

companies

# Compustat NA

Companies

only 106K with AT>0

# Compustat Cos with

public equity during the

year

# Compustat Cos with US

public equity securities

# CRSP Companies

1997 2,275 1,682 2,241 26 8 1,760 1,564 1,548 1,306

1998 5,351 4,096 5,221 109 21 4,600 4,048 3,960 3,285

1999 10,196 8,178 9,926 189 81 9,072 8,379 8,218 6,792

2000 11,200 9,122 10,593 335 272 9,801 9,220 8,923 7,075

2001 13,113 10,696 10,610 1,381 1,122 10,576 9,929 8,640 6,662

2002 15,035 12,335 10,861 2,080 2,094 11,271 10,546 8,574 6,383

2003 17,882 14,620 11,422 2,681 3,779 11,875 10,957 8,575 6,140

2004 20,990 17,224 11,565 3,051 6,374 12,095 11,307 8,688 6,113

2005 23,471 19,506 11,608 3,261 8,602 12,015 11,333 8,586 6,105

2006 26,894 22,808 11,736 3,318 11,840 11,934 11,290 8,507 6,057

2007 27,339 23,656 11,521 3,326 12,492 11,568 11,112 8,403 6,018

2008 26,606 23,537 11,370 3,265 11,971 10,748 10,372 7,788 5,746

2009 24,737 22,121 10,290 3,056 11,391 10,010 9,630 7,222 5,405

2010 11,414 10,437 3,657 1,073 6,684 3,438 3,396 2,538 1,978

Total 236,503 200,018 132,621 27,151 76,731 130,763 123,083 100,170 75,065

CIQ-PI Compensation Data Coverage


OTC Canadian

(1) (2) (3) (4) (5) (6) (7) (8) (9)

“Professional” Example: Lloyd Blankfein


Multiple functions per Company*Person relationship

Educational Records

Other “Director” affiliations

Biography Example: Lloyd Blankfein


Examples: 1)Links by Entity Types and

2)Educational Background

Links between Persons and the Following Entities

Entity Type Frequency Percent

Private Company 2,180,300 46.52%

Public Company 1,042,384 22.24%

Educational Institution 843,127 17.99%

Private Investment Firm 256,747 5.48%

Public Fund 222,395 4.75%

Private Fund/Investment Product 39,406 0.84%

Public Investment Firm 32,217 0.69%

Financial Service Investment Arm 16,123 0.34%

Foundation/Charitable Institution 15,556 0.33%

Trade Association 14,686 0.31%

Government Institution 12,377 0.26%

Corporate Investment Arm 8,775 0.19%


Number of CEOs and Professionals by Educational Affiliations University # of Professionals CEOs Harvard Business School 10,124 2,863

Stanford University 9,927 2,102

Harvard University 8,755 1,926

University of Pennsylvania

University of Pennsylvania - Wharton School 8,020 1,651

University of Pennsylvania - Others 4,170 707

Massachusetts Institute of Technology 6,147 1,207

University of California Berkeley 6,696 1,114

Columbia University 5,791 1,052

University of Michigan 6,539 1,016

Cornell University 5,667 950

University of Southern California 5,153 892

University Of British Columbia 3,222 837

New York University 4,602 796

The University of Chicago 4,739 788

University of California-Los Angeles 4,789 754

University of Toronto 3,996 738

University of Illinois-Urbana-Champaign 5,168 715

Yale University 3,952 678

Northwestern University - Kellogg 3,494 672

INSEAD 2,584 656

Princeton University 3,484 615

The University Of Western Ontario 2,652 614

University of Oxford 3,406 603

Network Clouds # of Persons

# people with 1 relationship 1,689,867

# people between 2 to 5 relationships 773,529

# people between 6 to 10 relationships 64,600

# people with greater than 10 relationships 22,987

Capital IQ - Capital Structure


Capital IQ Capital Structure

• CIQ Capital Structure is a Point-in-Time database which provides a detailed and comprehensive look into the capital structure issue-level components of a wide variety of companies around the globe

• Debt Capital Structure

Extensive coverage of debt capital structure for over 63,500 public and private companies (including subsidiaries) in more than 150 countries on an annual and interim basis back to 2001.

Over 11,000 US public entities covered (public companies, investment firms and public funds).

21 attributes of each debt component, such as

security type, seniority level, interest rate

maturity date, type of interest, redeemability

benchmark, secured flag, convertibility

currency, benchmark spread, and more

o Coverage

North America (US&Canada): 35% vs 65% International

Public : 80% (international) ; 63% (North America) with header flag


Capital IQ Capital Structure

Equity Capital Structure

36 equity capital structure data points include preferred shares, trust and partnership units,

share capital, minority and derived interests, convertibility information and shares

outstanding.

Covers over 82,000 public and select private companies in 155 countries back to 1997.

Flags for whether specific shares have voting rights and are authorized or not

Coverage

• North America (US&Canada) – 48%

• Public –79% (international) ; 68 % (North America) using header flag


Evolution of Company Coverage in CIQ DCS


0

2,500

5,000

7,500

10,000

12,500

15,000

17,500

20,000

22,500

25,000

27,500

30,000

32,500

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

US/Canada

International

CIQ DCS vs. Compustat coverage


1. Compustat NA Universe includes all companies reporting annual fundamentals with positive

total assets and positive total long-term debt. Sample excludes ADRs

2. CIQ Universe includes all US/Can firms covered by CIQ DCS

Example: excerpt from AMR Corp’s 10-K

Evolution of Debt Types in CIQ US Public companies

International public companies

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Notes Payable

Revolving Credit

Term Loans

FHLB Borrowings

Other Borrowings

Capital Leases

Bank Loans

Bonds and Notes

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Bank loans

Term Loans

Bonds and Notes

Revolving Credit

Other Borrowings

Notes Payable

Capital Leases

Bank Overdraft

Potential research venues using CIQ CIQ Capital structure database can help to shed more light on question like

How financial contracting between different stakeholders helps explain both cross-

sectional and time-series variation in leverage ratios

Better understanding of which debt components contribute most (least) to the speed and

nature of adjustment towards target leverage

How amount of total debt changes when various types of debt have differential expected

costs of distress

Refine our understanding of the relationship between asset liquidity, liquidation,

tangibility, profitability and leverage for different types of debt (Rauh and Sufi, 2010)

Do firms engage in debt specialization, i.e., do firms rely on only one type of debt

financing or use multiple sources of debt and how this decision is affected by firm ratings

(Colla et al., “Debt Structure” & “Debt Specialization”, 2009, 2010)

Analyst Data on WRDS


Working with Analyst data on WRDS

• I/B/E/S database from Thomson-Reuters o Both adjusted and unadjusted data

o Academic version does not carry management guidance (pre-announcement) data

• First Call from Thomson-Reuters o Contains management guidance from 1995

o Expected to be discontinued by TR next year

• Zacks, coming soon

o Estimates, Recommendations for over 19,200 active and inactive US and Canadian

firms (including Daily and Weekly consensus)

Annual and LTG – from 1978 to present; Quarterly – from 1982 to present

o Preannouncement History – from 1990 to present

o Surprise History - 1984 to present

o Sale forecasts (from Jan 2000) and Price target (from Dec 1997)

10/22/2011 65

Working with Analyst data on WRDS (cont.)

• Rounding issues in IBES adjusted data (Payne and Thomas, 2003) that may

lead to erroneous estimates of the forecast error.

o A research note on how to merge IBES Unadjusted Estimates with Reported

Actuals and to perform accurate split adjustment

• Relationship between Summary and Detail History

o A research note on Recreating IBES Summary based on Detail History File

provides evidence that Thomson-Reuters likely aggregates across the latest outstanding estimates at the broker, rather than analyst level

• Industry Recommendations in IBES (Kadan,Madureira,Wang and Zach,

2011)

o A research note explaining the details and containing a sample SAS code that can

be used to extract industry recommendations and categorize them into 3 groups (neutral, optimistic and negative, following KMWZ)

10/22/2011 66

http://wrds-web.wharton.upenn.edu/wrds/support/Data/_001Manuals and Overviews/_003I-B-E-S/_010Quick Links/A Note on IBES Unadjusted Data.pdf.cfm

http://wrds-web.wharton.upenn.edu/wrds/support/Data/_001Manuals and Overviews/_003I-B-E-S/_010Quick Links/A Note on Recreating Summary Statistics from Detail History.pdf.cfm

http://wrds-web.wharton.upenn.edu/wrds/support/Data/_001Manuals and Overviews/_003I-B-E-S/_010Quick Links/A Note on Industry Recommendations in IBES.pdf.cfm

Sample Research Applications using analyst data

10/22/2011 67

Post-Earnings Announcement Drift

– Calculate Standardized Earnings Surprises

(SUE) using either Compustat or IBES

Unadjusted Detail data

– Elaborates on differences b/w/ Compustat

GAAP earnings vs “street” earnings in IBES

– Form PEAD portfolios and assess the

abnormal performance for different universes

and time periods

Measuring Divergence of Investors’ Opinions

– Methodology to accurately compute Analyst

Forecast Dispersion using IBES Detail History

– Addresses the issue of staleness of forecasts

(McNichols and O'Brien, 1997) and incorporates

stopped and excluded estimates

– Explores the sensibility of different scaling factors

such as price and absolute mean forecast

FactSet Fundamentals in WRDS


FactSet Fundamental based on Worldscope


• Created out of a COPY of Thomson

Worldscope.

• Thomson updated database until April

2010.

• Since May 2020, FactSet.

• Available in WRDS.

Comparing International Coverage

•Compustat Global , BVD Osiris and

FactSet (Worldscope).

•Number of Countries

•Number of Companies


Country Coverage


Company Coverage


Small Firms make a difference


Com

pusta

t

Glo

bal

Log(Total Assets) Log(Sales)

Fa

ctS

et

Osir

is

Today’s Session

• Research Applications & Macros

• WRDS SEC Analytics Suite

• New TAQ Datasets that makes

research easy

• Capital IQ Databases

• Analyst Data.

• International data. Factset.

Wharton Research Data Services 74 10/22/2011

Thank You

Thank You

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