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Darina Slattery TKE’02 30th August 2002
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Automatic Analysis of Corporate Financial Disclosures Darina M. Slattery
University of Limerick Ph.D. Postgraduate Student
Richard F.E. Sutcliffe University of Limerick
Eamonn J. Walsh University College Dublin
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Research Objective To investigate the correlation between
the release of disclosure information and share price resonses, and to develop a system that will analyse such disclosure information and predict the likely share price response accordingly
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Principal Stages of Research Identify Interesting Content in Disclosures
Use Classification Techniques to Predict the likely Share Price Response, based on Interesting Content identified
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Definition of Financial Terms Corporate Financial Disclosures
Securities & Exchange Commission (SEC)
EDGAR
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Definition of Financial Terms SIC Code
CIK Code
Ticker Symbol
Registrant
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Sources of Financial Information Disclosures
Historical Share Price Data
Press Releases
Industry Trends
Speculation
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SEC & EDGAR: Background (1/2) The Securities Act of 1933 & the Securities
Exchange Act of 1934: Require all Public Domestic Companies
to disclose and file Specific Periodic & Annual Reports with the SEC
As of May 1996, all SEC disclosures must be filed on EDGAR and thus made available online at http://www.sec.gov/edgarhp.htm
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SEC & EDGAR: Background (2/2) EDGAR can be accessed by:
Web Browser Anonymous File Transfer Protocol (FTP)
EDGAR Search Facilities: General-Purpose Searches Special-Purpose Searches
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EDGAR Disclosures Format Dictated by Law
Plain Text or HTML only
Certain Limitations on HTML Tags For Consistency
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EDGAR Form Types (1/2) Form 10-Q
Quarterly Report Continuing View of the Company Due within 45 Days after Quarter Close
Form 10-K Annual Report Comprehensive Overview of the Company Due within 90 Days after End of Fiscal Year
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EDGAR Form Types (2/2) Form 8-K
Current Report Reports the Occurrence of any Material
Events and Corporate Changes Of interest to Shareholders & Potential
Investors Due within 5 or 15 Days after the Event
Occurrence, depending on Event
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Stages Undertaken To-Date Obtained Suitable Data Set
Analysed Structure of Form 8-K’s
Prepared Content for Classification
Attempted to Classify Documents by Likely Share Price Response
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Data Set Obtained 567 Form 8-K disclosures in SIC 7372
Filing Date URL Share Price Response around Filing Date
Up Down Nochange
219/ 567 Disclosures Chosen for Experiments Categorised by Share Price Response
80% of each Category used as Training Data 20% of each Category used as Test Data
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Structural Analysis Header Items 1-9
Item 1: Changes in Control of Registrant Item 2: Acquisition or Disposition of Assets Item 3: Bankruptcy or Receivership Item 4: Changes in Registrant’s Certifying Accountant Item 5: Other Materially Important Events Item 6: Resignations of Registrant’s Directors Item 7: Financial Statements and Exhibits Item 8: Change in Fiscal Year Item 9: Regulation FD Disclosure
Appendices
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Content Preparation: Wordsmith
On June 2, 1998, XXX Corporation announced in a press release the signing of an Acquisition Agreement and Plan of Merger …On May 2, 2000, XXX Corporation announced in a press release the sale of the outstanding capital stock of …
On April 17, 1997, XXX Corporation signed an Agreement and Plan of Merger …
agreement and plan of merger
announced in a press release
the outstanding capital stock of…
Note: Sorted by frequency
in descending order
219 Disclosures
…
Large Phrase ListWORDSMITH
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Content Preparation: Tokenisation
‘agreement’,’and’,’plan’,’of’,’merger’‘announced’,’in’,’a’,’press’,’release’‘the’,’outstanding’,’capital’,’stock’,’of’…
agreement and plan of merger
announced in a press release
the outstanding capital stock of…
Note: Sorted by frequency in descending order
Large Phrase List Tokenised Phrase List
Note: 219 Disclosures are also Tokenised
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Content Preparation: Compound Search Trees
‘agreement’,’and’,’plan’,’of’,’merger’‘announced’,’in’,’a’,’press’,’release’‘the’,’outstanding’,’capital’,’stock’,’of’…
COMPOUND SEARCH TREE GENERATOR
[agreement, [and, [plan, [of, [merger, []]]]]]
[announced, [in, [a, [press, [release, []]]]]]
[the, [outstanding, [capital, [stock, [of, []]]]]]
…
Note: At this stage, the phrase list is cut off at 100, 1000 & 10000 phrases for the three experiments
Tokenised Phrase List
Search Tree
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Content Preparation: Compound Noun Matching (1/2)
‘on’,’june’,’2’,’1998’,’xxx’,’corporation’,’announced’,’in’,’a’,’press’,’release’,…‘on’,’may’,’2’,’2000’,’xxx’,’corporation’,’announced’,’in’,’a’,’press’,’release’,…‘on’,’april’,’17’,’1997’,’xxx’,’corporation’,’signed’,’an’,’agreement’,’and’,’plan’…
…
Search Tree
COMPOUND NOUN
MATCHING
219 Disclosures
[agreement, [and, [plan, [of, [merger, []]]]]]
[announced, [in, [a, [press, [release, []]]]]]
[the, [outstanding, [capital, [stock, [of, []]]]]]
…
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Content Preparation: Compound Noun Matching (2/2)
announced_in_a_press_releaseagreement_and_plan_of_merger…
announced_in_a_press_releasethe_outstanding_capital_stock_of…
agreement_and_plan_of_merger…
COMPOUND NOUN
MATCHING
219 DisclosuresWith Single Token
Phrases
…
The Number of Single Token
Phrases is Determined by the Length of
Phrase List Used (100, 1000 or
10000 Phrases)
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Content Preparation: Overview
On June 2, 1998, XXX Corporation announced in a press release the signing of an Acquisition Agreement and Plan of Merger …On May 2, 2000, XXX Corporation announced in a press release the sale of the outstanding capital stock of …
On April 17, 1997, XXX Corporation signed an Agreement and Plan of Merger …
219 Disclosures
…
announced_in_a_press_releaseagreement_and_plan_of_merger…
announced_in_a_press_releasethe_outstanding_capital_stock_of…
agreement_and_plan_of_merger…
…
219 Disclosures With Single Token Phrases
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Classification: DTS System (1/2) The C4.5 Decision Tree System (DTS)
A Machine Learning Algorithm
Derives Decision Trees Set of Records (i.e. Set of Disclosures)
Non-Categorial Attributes Categorial Attribute
Files Required File.names File.data File.test
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Classification: DTS System (2/2) File.names
Defines Non-Categorial & Categorial Attributes
File.data & File.test Training & Test Files Take Same FormatTRUE,FALSE,FALSE,…,UP
FALSE,TRUE,TRUE,…,DOWN
FALSE,FALSE,TRUE,…,NOCHANGE
…
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Classification: IIS System The Inverted Index System (IIS)
A Conventional Information Retrieval (IR) System
But used as a Classification System Here Query = Disclosure Only 3 Documents in Document Collection
Ups Downs Nochanges
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Classification Experiments Conducted Three Experiments
DTS & IIS used in each experiment
First Experiment 100 Most Frequently Occurring Phrases
Second Experiment 1,000 Most Frequently Occurring Phrases
Third Experiment 10,000 Most Frequently Occurring Phrases
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Classification ResultsN-Most Freque
nt Phrases
DTS IIS (Default
up)
IIS (Default down)
IIS (Ignore default)
100 38% 36% 38% 45%
1,000 44% 31% 38% 34%
10,000 42% 40% 42% 42%
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Conclusions & Next Steps How can we Improve the Classification
Results? Identify Significant Disclosures Identify Significant Content Increase Data Set Two-Way Classification?
Automate Partitioning of Relevant Disclosures
Automate Scanning for Significant Content
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Contact DetailsMs. Darina Slattery, B.B.S. M.Sc.
Dept. of Computer Science & Information Systems,University of Limerick,
Limerick,Ireland
Tel: +353-61-213551Email: [email protected]