The Importance of Corporate Disclosure: How ... - MIT...

The Importance of Corporate Disclosure:How Market Transparency Affects The Firm's

Financial Health

SP Kothari and James ShortMIT Sloan School of Management

November, 2003

What Did We Study?

• What is the effect of disclosures made by management, analysts, and the financial press on the equity cost of capital?

• What are the implications of changes in the volume, content and channel of formal and informal disclosure on the equity cost of capital?

• What are the implications of the results found?

How Did We Study It? 1

• Model Construction– We built two models, an information model and a

financial model, and linked them empirically to test for the effects of disclosure source and content on equity cost of capital

• Data– We built a comprehensive disclosure database

• 887 companies in four industry sectors: Financial, Pharmaceutical, Technology, Telecommunications

• 3 disclosure channels, corporate, investment analysts, business and financial press

• 326, 357 texts were downloaded in their entirety, over 1 million pages of text, for the period 1996-2001

How Did We Study It? 2

• Method– We built a business category dictionary of terms

to filter the original disclosure database– We wrote our own programs to filter and organize

the text database for content analysis (the database was too large for off-the-shelf programs)

– We used the most highly-regarded analysis software for large-scale content analysis – the General Inquirer (text mapping software)

• Tools– We wrote our own programs to automate and

verify text downloaded from the four electronic databases accessed, Dow Jones Industrial, Factiva, Investex, and SEC Edgar

What Did We Find? 1Results for

Management

• Our first set of results concerns the impact of positive and negative news disclosure by management on equity cost of capital, for all companies and for all industry sectors

• Positive and strongly positive statements made by management are discounted by the market, and do not materially affect cost of capital

• Negative and strongly negative statements made by management cause the cost of capital to go up


Management

• This result is consistent across all industries and industry sectors

• Interpretation: when negative statements are made, these are made in the context of a positive bias, therefore, the market responds and strongly weights negative news

What Did We Find? 3Results forAnalysts

• Our second set of results concerns the impact of positive and negative news disclosure by analysts

• We found that both positive and negative disclosures by analysts are discounted by the market

• Moreover, the strength of impact of analyst disclosure is less than that for management and for the financial press

What Did We Find? 4Results forAnalysts

• Statistically, analyst disclosure has greater impact on stock returns and analyst forecast error, less on cost of capital

• These results are consistent across industry sectors• Interpretation: Intuitively, these results suggest

analysts have credibility problems. Their statements are more heavily discounted by the market, their impact is therefore less.


Press

• Our third set of results concerns the impact of positive and negative news disclosure by the business press

• We found that positive and strongly positive disclosure statements made by the business press affect cost of capital, causing it to decrease

• We found that negative and strongly negative disclosure statements made by the press affect cost of capital, causing it to increase


Press

• These results are consistent across industry sectors

• Interpretation: Intuitively these results suggest that the press is seen by the market as less biased. The direction and strength of press disclosure affects cost of capital in the classically hypothesized way – positive disclosure tends to reduce cost of capital, negative disclosure tends to increase it.

What Are the Implications? 1

• This is the first comprehensive research study to empirically test the impact of disclosure on the equity cost of capital, and find support for the core hypothesis. Disclosure source and intensity affects cost of capital.

• With regard to corporate disclosures, our results can be interpreted to question the effectiveness of current practices of corporate communications. We found the market discounts positive news disclosure, and strongly weights negative disclosure, taking into account a positive (agency) bias.


• Our results stress the importance of a clear, consistent, timely and comprehensive corporate disclosure policy. They also suggest that the way corporate communications offices are structured (centralized or distributed) is an important management issue.


• With regard to analysts, our results highlight that analysts have credibility problems. We found that both positive and negative disclosures by analysts are discounted by the market.

• For analysts, the implications are that they must address questions of agency and incentives if they wish to improve credibility in the market


• Our results can be interpreted to question the effectiveness of current corporate practices in disclosing specialized information to analysts. Many companies commit significant resources to providing specialized information to analysts through management briefings, etc., with the goal of market effect. Our results suggest such assumptions may benefit from management attention and more systematic study.


• For investors, the implications are that analysts do not perform a specialized, unbiased role in company evaluation. Rather, our results are consistent with analysts exercising a specialized, biased role.


• Our results for the business press support their important balancing role in the marketplace. We found that their effect on equity cost of capital was consistent in direction and intensity relative to those by management and analysts. When press disclosure was positive, cost of capital went down; when press disclosure was negative, cost of capital went up.


• For investors, the implication is that evaluation of companies in the business press is an important asset in disclosure evaluation

• For management, our results suggest that company disclosure practices should focus as much on the business press as any other intermediary in the market, and arguably more

What Next?

• Our results suggest future research in four areas:– Expansion of the database to include additional

years and and disclosure channels (example: public internet and ratings)

– Specialized sectoral analysis including analysis of strategic groups and chains

– Event history analysis– Expanded Information Modeling and Content

Analysis

PROJECT HISTORY

APPENDIX

Project Structure, OrganizationInformation Model

J ShortFinancial Model

SP Kothari

Tools forAutomated Data

Extraction, Parsing,Compilation

Main DatabaseDownload Team

Dow Jones, Investex,SEC Edgar, Other (Specialized)

Data Dictionary &Statistical AnalysisNVIVO, GeneralEnquirer, Manjara

Industry Sub-SamplesTelecommunications

Wireless(US, Korea )

Corey McCaffreyKalani OshiroStanley Woods

Mitul MehtaKalani Oshiro

Tanis FidelholtzShiva RameshStanley Woods

Mitul MehtaKalani OshiroStanley WoodsTanis FidelholtzShiva Ramesh

US: Mitul MehtaKalani OshiroStanley Woods

Korea: Elisa RahJoy Lee

Future Module Future Module

ManjaraClusteringAlgorithm

High TechVenture Capital

Database (250 firms)

Information Value Framework (PWC)

Management’s Viewof Company’s Value

Quality of Information

Importance of anInformation Measure

How actively a measureis communicated

Importance of anInformation Measure

How adequately ameasure is

communicated

Market’s Viewof Company Value

Value Gap

Quality Gap

Understanding Gap

Information GapReporting Gap

Perception Gap

Flow of Information and Capital in Disclosure

Investors

InformationIntermediaries

FinancialIntermediaries

BusinessFirms

Flow of Information

Auditors &Accounting Regulators

Regulators andFinancial Institutions

Flow of Capital

Flowchart of Content AnalysisTheory and Rationale

(disclosure, communications research)

Conceptualization(model, hypotheses)

Operationalization(variables, sample, coding)

Coding Schema(new dictionary construction)

Coding Schema(use of secondary dictionaries)

Analysis(apply schema to generate frequencies)

Analysis(apply schema to generate weight samples)

Hypothesis Testing, Reporting(analysis of main database, sub-samples

and reporting)

New Dictionary Construction Use Secondary Dictionaries

Disclosure DatabaseDisclosure Data For 887 Companies In Four Sectors Was Downloadedfrom Four Electronic Databases and Supplemental Content Sources,

For 6 Year and 10 Year Time SeriesSectorsBy

Electronic DBs

Tech197 Firms

Telecom395 Firms

Pharma72 Firms

Financial225 Firms

DowJones

(1996-2001)Complete

Complete

CompleteComplete

CompleteComplete

Complete

Complete Complete

Complete

Complete

Complete Complete

Complete

Complete Complete

Investex(1992-2001)

Factiva*(1996-2001)

SECEdgar

(1996-2001)

*Factiva replaced DJI and Investex in the MIT Library system in May 2003. It contains several additional international titles from the Reuters News Services which are being added to the master content dataset.

Project Flow for Disclosure Analysis

Main Database Analysis Sequence

Business Category Dictionary

Analysis of 10k, 10QStatements:Business ModelForward Looking (+)Risk Factors (-)Quality of GovernanceCustomer SatisfactionMarket Recognition and Branded Image

Statements of market recognition, power and consistency of branded

image, measures of consumer confidence and trust in branded image

Statements of Market Risk,Industry Analysis and

Competitive Forces

Statements of firm-level strategy intent, product market performance,

performance of business strategy model in use

Statements of human and organizational capital, quality of

management performance, corporate governance and leadership

Count & FreqsBusinessCategory Dictionary

Sub-sample Sub-sampleIndustry Sector:Lead Company

MainDatabase

3. Filtered Database(6 categories)

GeneralEnquirer

4.

5.Freq Matrix

(weights)

1.

2.

EconometricAnalysis

(cost of capital, etc.)Statements of federal government

regulation enacted or pending influential to firm competitiveness,

product market performance, and/or disclosure practices.

• Build Main Database and Industry Sub-samples• Build Information Analysis (Content) Dictionary• Select Industry Sector and Identify Lead Company in Sector• Select All Disclosure Information For Lead Company• Analyze Lead Company For Terms & Word Groupings Used in Forward Looking Statements• Revise Analysis Dictionary Based on Lead Company Analyses• Conduct Analysis on Industry Sub-samples and Main Database

Statements of CorporateAnd Business Unit Financial

Performance, Stock Transactions

Analysis Steps in Constructing Measures of Positive and Negative Coverage of Each Company by Source of

DisclosureDisclosure Texts by Source(management, analyst, press)

Then, Parsed Texts Are Run Through The General Inquirer

Statements of market recognition, power and consistency of branded image,

measures of consumer confidence and trust in branded image

Statements of Market Risk,Industry Analysis and

Competitive Forces

Statements of firm-level strategy intent, product market performance, performance

of business strategy model in use

Statements of human and organizational capital, quality of management

performance, corporate governance and leadership

Statements of federal government regulation enacted or pending influential to firm

competitiveness, product market performance, and/or disclosure practices.

Statements of corporate and business unitfinancial performance

The General Inquirer ProgramMatches Words in Disclosure Texts

Against Dictionary of Wordsand Word Meanings for

Positive and NegativeCoverage, Producing Raw Counts

And Percentages of PositiveAnd Negative Words As Fraction

Of All Words in Texts

Producing Text FilesOrganized by Source of Disclosure

By Business Category

Percentages of Positive andNegative Word Frequencies

Calculated for Each DisclosureText Are Then Averaged

Across Time For EachBusiness Quarter

(1996-2001)Are Parsed By Matching

Source Texts Against Six CategoryDictionary of Terms

These Mean ScoresAre Then Averaged

Across Business Categories,Producing for Each

Disclosure Text,A Frequency Measure

Of Positive and NegativeCoverage, by Source, forAll Disclosures AveragedBy Quarter by Business

Category

Positive and NegativeScores Then Entered Into

Financial Models

Factors in Information Weight Calculations(Revised 10 factor design June 2003)

31 41 511 40 50 602110 2011 30

Org Capital IP(Group 3)

Brand Image(Group 4)

Regulation(Group 6)

Fin Performance(Group 5)

Market(Group 1)

Firm Strategy(Group 2)

Posi

tiv

Neg

ativ

Eval

@

Tim

e@

Posi

tiv

Neg

ativ

Eval

@

Tim

e@

Posi

tiv

Neg

ativ

Eval

@

Tim

e@

10 General InquirerContent Categories

(Factors)

1 092 10


(Factors)

1 092 10


(Factors)

1 092 10General Inquirer Content Categories (Factors):Positiv GoalNegativ MeansEcon@ CompletLegal Eval@ComForm Time@

Weight Factor Definitions, Notes(from General Inquirer, Harvard University)

• Positiv– Words and word groups associated with

a positive outlook• Negativ

– Words and word groups associated with a negative outlook

• Econ@– Words associated with an economic,

commercial, industrial or business orientation, including roles, collectivities, acts, abstract ideas and symbols, including references to money. Includes names of common commodities in business

• Legal– Words relating to legal, judicial, or

police matters• ComForm

– Words relating to the form, format or medium of the communication transaction

• Goal– Names of end-states towards which striving

is directed• Means

– Words denoting objects, acts or methods utilized in attaining goals

• Complet– Words indicating that goals have been

achieved, apart from whether the action may continue

• Evalu@– Words which imply judgment and

evaluation, whether positive or negative, including means-ends judgments

• Time@– Time@ 273 words indicating a time

consciousness, including when events take place and time taken in an action. Includes velocity words as well. There is also a more restrictive TIME category (75 words) used as a marker for disambiguation.

Weight Factors, Notes

• Factor weight matrix reduced to ten (10) content categories (word sense and word meanings), calculated for full database and for six business categories (market, firm, org capital, brand image, fin performance and regulatory)

• Reduction undertaken for three reasons: same precision (essentially the same as the larger number of factors), estimation requirements for the financial model (adequate degrees of freedom for testing of hypotheses), and processing time / efficiency (extensive for multiple factor modeling).

Example Analysisfile wordcount leftovers Positiv Negativ Strong Weak Ovrst Undrst Econ@ ExchIBM - 2001-01-01 - Barron's .txt 3146 403 136 104 303 64 145 79 174 19IBM - 2001-01-02 - New York Times Abstracts .txt 68 13 3 4 5 1 1 1 8 0IBM - 2001-01-02 - The Wall Street Journal .txt 1826 235 49 65 171 50 111 43 153 7

Downloaded Articles for IBM49 Sources6 Years (1996-2001)4000 Articles (35mb)

Word classifications according to General Inquirer Dictionary182 AttributesExamples above: Positive, Negative, etc.

MethodStep 1: Classify text files in non-contextual attribute matrixStep 2: Reduce the attribute matrix by clustering affective terms by business classification anchorsStep 3: Produce weights based on scaled importanceStep 4: Create weights for all companies in the sample (weight = information importance) 4 categories, 12 factors

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