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

Transcription

1 The Importance of Corporate Disclosure: How Market Transparency Affects The Firm's Financial Health SP Kothari and James Short MIT Sloan School of Management November, 2003

2 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?

3 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

4 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

5 What Did We Find? 1 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 Results for Management 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

6 What Did We Find? 2 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 Results for Management

7 What Did We Find? 3 Results for Analysts 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

8 What Did We Find? 4 Results for Analysts 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.

9 What Did We Find? 5 Our third set of results concerns the impact of positive and negative news disclosure by the business press Results for 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

10 What Did We Find? 6 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. Results for Press

11 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.

12 What Are the Implications? 2 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.

13 What Are the Implications? 3 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

14 What Are the Implications? 4 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.

15 What Are the Implications? 5 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.

16 What Are the Implications? 6 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.

17 What Are the Implications? 7 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

18 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

19 PROJECT HISTORY APPENDIX

20 Project Structure, Organization Information Model J Short Financial Model SP Kothari Tools for Automated Data Extraction, Parsing, Compilation Main Database Download Team Dow Jones, Investex, SEC Edgar, Other (Specialized) Data Dictionary & Statistical Analysis NVIVO, General Enquirer, Manjara Industry Sub-Samples Telecommunications Wireless (US, Korea ) Corey McCaffrey Kalani Oshiro Stanley Woods Mitul Mehta Kalani Oshiro Tanis Fidelholtz Shiva Ramesh Stanley Woods Mitul Mehta Kalani Oshiro Stanley Woods Tanis Fidelholtz Shiva Ramesh US: Mitul Mehta Kalani Oshiro Stanley Woods Korea: Elisa Rah Joy Lee Future Module Future Module Manjara Clustering Algorithm High Tech Venture Capital Database (250 firms)

21 Information Value Framework (PWC) Management s View of Company s Value Quality of Information Value Gap Market s View of Company Value Quality Gap Importance of an Information Measure Reporting Gap How actively a measure is communicated Understanding Gap Perception Gap Importance of an Information Measure Information Gap How adequately a measure is communicated

22 Flow of Information and Capital in Disclosure Flow of Information Investors Flow of Capital Information Intermediaries Financial Intermediaries Auditors & Accounting Regulators Business Firms Regulators and Financial Institutions

23 Flowchart of Content Analysis Theory and Rationale (disclosure, communications research) Conceptualization (model, hypotheses) Operationalization (variables, sample, coding) New Dictionary Construction Coding Schema (new dictionary construction) Use Secondary Dictionaries 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)

24 Sectors By Electronic DBs Dow Jones ( ) Investex ( ) Disclosure Database Disclosure Data For 887 Companies In Four Sectors Was Downloaded from Four Electronic Databases and Supplemental Content Sources, For 6 Year and 10 Year Time Series Tech 197 Firms Telecom 395 Firms Pharma 72 Firms Financial 225 Firms Factiva* ( ) SEC Edgar ( ) *Factiva replaced DJI and Investex in the MIT Library system in May It contains several additional international titles from the Reuters News Services which are being added to the master content dataset.

25 Project Flow for Disclosure Analysis Main Database Analysis Sequence Sub-sample Sub-sample Business Category Dictionary 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 market recognition, power and consistency of branded image, measures of consumer confidence and trust in branded image Statements of Corporate And Business Unit Financial Performance, Stock Transactions Statements of federal government regulation enacted or pending influential to firm competitiveness, product market performance, and/or disclosure practices. Industry Sector: Lead Company Analysis of 10k, 10Q Statements: Business Model Forward Looking (+) Risk Factors (-) Quality of Governance Customer Satisfaction Market Recognition and Branded Image Main Database 4. Business Category Dictionary 3. Filtered Database (6 categories) 5. General Enquirer Count & Freqs Freq Matrix (weights) Econometric Analysis (cost of capital, etc.) 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

26 Analysis Steps in Constructing Measures of Positive and Negative Coverage of Each Company by Source of Disclosure Disclosure Texts by Source (management, analyst, press) Are Parsed By Matching Source Texts Against Six Category Dictionary of Terms 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 market recognition, power and consistency of branded image, measures of consumer confidence and trust in branded image Statements of corporate and business unit financial performance Statements of federal government regulation enacted or pending influential to firm competitiveness, product market performance, and/or disclosure practices. Producing Text Files Organized by Source of Disclosure By Business Category Then, Parsed Texts Are Run Through The General Inquirer The General Inquirer Program Matches Words in Disclosure Texts Against Dictionary of Words and Word Meanings for Positive and Negative Coverage, Producing Raw Counts And Percentages of Positive And Negative Words As Fraction Of All Words in Texts Percentages of Positive and Negative Word Frequencies Calculated for Each Disclosure Text Are Then Averaged Across Time For Each Business Quarter ( ) These Mean Scores Are Then Averaged Across Business Categories, Producing for Each Disclosure Text, A Frequency Measure Of Positive and Negative Coverage, by Source, for All Disclosures Averaged By Quarter by Business Category Positive and Negative Scores Then Entered Into Financial Models

27 Factors in Information Weight Calculations (Revised 10 factor design June 2003) Market (Group 1) Firm Strategy (Group 2) Org Capital IP (Group 3) Brand Image (Group 4) Fin Performance (Group 5) Regulation (Group 6) Positiv Negativ Eval@ Time@ Positiv Negativ Eval@ Time@ Positiv Negativ Eval@ Time@ General Inquirer Content Categories (Factors) General Inquirer Content Categories (Factors) General Inquirer Content Categories (Factors): Positiv Goal Negativ Means Econ@ Complet Legal Eval@ ComForm Time@ General Inquirer Content Categories (Factors)

28 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.

29 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).

30 Example Analysis file wordcount leftovers Positiv Negativ Strong Weak Ovrst Undrst Exch IBM Barron's.txt IBM New York Times Abstracts.txt IBM The Wall Street Journal.txt Downloaded Articles for IBM 49 Sources 6 Years ( ) 4000 Articles (35mb) Word classifications according to General Inquirer Dictionary 182 Attributes Examples above: Positive, Negative, etc. Method Step 1: Classify text files in non-contextual attribute matrix Step 2: Reduce the attribute matrix by clustering affective terms by business classification anchors Step 3: Produce weights based on scaled importance Step 4: Create weights for all companies in the sample (weight = information importance) 4 categories, 12 factors