1 / 69

Professor Joshua Livnat, Ph.D., CPA 10-76 K-MEC New York University 44 W. 4th St. NY NY 10012

Professor Joshua Livnat, Ph.D., CPA 10-76 K-MEC New York University 44 W. 4th St. NY NY 10012 Tel. (212) 998-0022 Fax (212) 995-4004 jlivnat@stern.nyu.edu Web page: www.stern.nyu.edu/~jlivnat. The Standard & Poors’ Filing Dates Database – Research Applications. Overview.

Télécharger la présentation

Professor Joshua Livnat, Ph.D., CPA 10-76 K-MEC New York University 44 W. 4th St. NY NY 10012

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Professor Joshua Livnat, Ph.D., CPA 10-76 K-MEC New York University 44 W. 4th St. NY NY 10012 Tel. (212) 998-0022 Fax (212) 995-4004 jlivnat@stern.nyu.edu Web page: www.stern.nyu.edu/~jlivnat The Standard & Poors’ Filing Dates Database – Research Applications

  2. Overview • The need for the database. • Description of the database. • Three research applications.

  3. Data Acknowledgements • Charter Oak Investment Systems Inc. for providing the preliminary and original Compustat quarterly data. • http://www.charteroaksystems.com/ • S&P’s Filing Dates Database. • Thomson Financial for providing earnings forecasts available through the Institutional Brokers Estimate System.

  4. The Market Need • The SEC EDGAR database contains a wealth of information on listed companies: • Periodic reports; Form 10-K, Form 10-Q • Special reports; Form 8-K • Proxy statements; DEF14 • Registration statements; S-1 through S-4 • Insider trading; Forms 3 and 4 • The EDGAR database contains the filing dates of the various forms. Ideal for event studies.

  5. The Market Need (continued) • The SEC EDGAR database identifies companies by a unique identification code, CIK. • The CIK is not linked to the customary research databases such as Compustat, CRSP, or IBES. • The Compustat Expressfeed and Research Insight databases contain CIK’s, but those are for live companies. Using them in research will cause survivorship bias. • Commercial EDGAR vendors such as EDGAR Online and 10K Wizard offer linking of CIK’s to ticker symbols or even CUSIP’s. Those are typically good for live companies.

  6. The Market Need (continued) • Even with perfect matching between CIK and some other identifiers, there is a need to extract information from SEC filings: • Financial statement period-end dates for Forms 10-K and 10-Q. • Reason for filing Form 8-K.

  7. The S&P Filing Dates Database • Matching Compustat’s GVKEY for live and inactive companies to CIK’s using the Point-In-Time database. • Extracting all SEC EDGAR filing dates for each GVKEY. • Extracting information from key filings to enable research.

  8. Digression – The PIT Database • The Compustat quarterly database gets rewritten continuously when firms update the information on previous quarters: • Mergers and acquisitions. • Divestitures. • Restatements. • Disclosure of quarterly results in the 10-K Form. • Compustat captures preliminary information (from firms’ preliminary earnings announcements) and final information from SEC filings.

  9. Digression – The PIT Database • Charter Oak collected the weekly CD-Rom’s sent by Compustat to its clients. From those, it constructed: • A preliminary database, which contains information released by companies and captured by Compustat before it became final. • A PIT database, which contains the information that Compustat users would have had at any given month-end. • Both databases are now available through WRDS.

  10. Digression – The PIT Database • Research using the PIT database: • Earnings and revenues surprises, Jegadeesh and Livnat, JAE 2006. • Post earnings announcement drift for firms covered by IBES, Livnat and Mendenhall, JAR 2006. • Firms that change earnings between preliminary to SEC filings, Hollie, Livnat and Segal, JOPM 2005.

  11. The preliminary and PIT databases

  12. Matching GVKEY-CIK • Identified all GVKEY’s on the PIT database for firms that had a market value in excess of $1million at quarter-end. • Matched these firms to CIK’s, and checked each match if the name on EDGAR and Compustat was not identical. • A few GVKEY’s were not matched. Typically, not listed firms, or Canadian firms.

  13. Extracting SEC Data • Using Text-Mining techniques, extracted certain information from filings. • The report date from periodic reports: • The financial statement period-end date. • The date for the annual shareholders meeting from proxy statements. • The date on which the reported event in a special report Form-K occurred. • Reasons for filing a special report on Form 8-K.

  14. The S&P Filing Dates Database

  15. Periodic Reports

  16. Proxy Statements

  17. Form 8-K

  18. Ford – All Filings

  19. Recent Research Applications • Quarterly accruals or cash flows? Forthcoming in FAJ. • Uses exact filing dates for 10-Q and 10-K to construct portfolios. • Tone of MD&A section. • Market reactions to Form 8-K filings. • Uses filing dates and reasons for filing. • Proxy filings and annual meeting dates. • Uses the filing and report dates for proxy filings in the database.

  20. Joshua Livnat Department of Accounting Stern School of Business Administration New York University 10-76 Kaufman Management Education Center 44 W. 4th St. New York City, NY 10012 (212) 998–0022 jlivnat@stern.nyu.edu German Lopez-Espinosa, University of Navarra Rolling Quarterly Accruals and Cash Flows: Universe and Industry Analysis

  21. Overview • Objectives: • Examine whether quarterly accruals (or rolling four-quarter accruals are superior to net operating cash flow (OCF). • Examine whether accruals are superior to OCF within an industry.

  22. Overview (Continued) • Methodology: • Associate quarterly accruals and OCF, as well as rolling four-quarter accruals and OCF, with future returns. Returns can be for the immediately subsequent quarter or for a whole year. • Prior studies typically use annual accruals and annual returns. • Associate accruals and OCF with future returns within industries to determine which measure is superior within that industry.

  23. Overview (Continued) • Results: • OCF is typically a superior measure to accruals. It is inferior to accruals only in the fourth quarter when the return window is annual and the signal is based on rolling four quarters. • Accruals are a relevant signal when the return window is annual, or when accruals are based on rolling four-quarters. • OCF is a value-relevant signal whether the return window is one quarter or annual, and whether based on one quarter or rolling four quarters. • Within an industry OCF is superior to accruals.

  24. Data Acknowledgements • Charter Oak Investment Systems Inc. for providing the Point-In-Time (PIT) Compustat quarterly data. • http://www.charteroaksystems.com/ • S&P’s SEC Filing Dates Database.

  25. Definition - Accruals • Accruals = Net Income – Net Operating Cash Flow. • Represents investments in net current assets (such as inventories and receivables), as well as adjustments for accounting items that are not cash items (such as depreciation and deferred taxes). • Accruals are typically negative; net income is after depreciation whereas net operating cash flow is not.

  26. Sloan (1996) – Accrual Anomaly

  27. Quarterly Accruals • The accruals anomaly was first documented for annual accruals. • It was well replicated by many follow-up studies. • Companies disclose quarterly accruals too. • Professional investors likely want to use quarterly accruals instead of waiting for annual accruals.

  28. Institutional Considerations • Most firms announce preliminary earnings after quarter-end, but do not disclose net operating cash flow in this announcement. • Firms then file their 10-Q/10-K Forms with the SEC, which include net operating cash flows. • Easton and Zmijewski (1993) and Griffin (2003) show that most firms file on the last day or two of the allowed period. Quarter End Preliminary Earnings SEC Filing 27 days 17 days

  29. Quarterly Accruals Research • Earnings are typically known before accruals. Most firms disclose accruals only in their SEC filings. • SEC filing dates are not in the Compustat database. • Most prior studies on accruals did not have access to SEC filing dates, so they could not test for quarterly accruals.

  30. Accruals and OCF • Accruals and OCF are negatively correlated, but the correlation is not –100%. • An investor can construct portfolios based on accruals or OCF (or both). • Desai, Rajgopal and Venkatachalam (2004) show that OCF dominates accruals and that accruals are not incrementally valuation relevant beyond OCF. • Cheng and Thomas (2006) and Barone and Magilke (2006) show that accruals are incrementally valuation relevant beyond OCF.

  31. Open Research Questions • Are accruals incrementally valuation relevant beyond OCF when using quarterly data? • Should accruals (and OCF) be calculated using current quarter data or rolling four quarters? • What is the optimal holding period (one or four quarters)? • Are accruals (and OCF) more or less effective in certain fiscal quarters? • Are accruals (or OCF) effective within an industry?

  32. Sample • Firms with filing dates that are within 55 (100) days after the balance sheet date. • Firms that are on the CRSP database. • Market value and total assets are in excess of $1 million; available data on net income and OCF; available total assets at prior quarter. • Eliminate firms with the extreme 0.5% of returns.

  33. Variables • Accruals are net income minus net operating cash flow. • Accruals and OCF are scaled by average total assets during the quarter. • Scaled accruals and OCF are winsorized to fall in the range [-1,+1]. • Excess returns are buy and hold returns (BHR) on the specific firm minus the BHR on a matched Fama and French size and B/M portfolio (6 groups).

  34. Holding Period • Buy and Hold returns from two days after the SEC filing date through one day after the subsequent quarter’s preliminary earnings announcement, or 90 days if unavailable. • For an annual return window, it is from two days after SEC filing date for quarter t through one day after the preliminary earnings announcement for quarter t+4, or 360 days if unavailable.

  35. Rolling Four-Quarter Data • Using the Point-In-Time database to ensure these data were what investors knew at the time. • Rolling four-quarter data in the fourth fiscal quarter are equal to annual accruals, which were used by prior annual studies.

  36. Analysis • Our analysis is based on estimating regression equations with future excess returns as the dependent variable and signal ranks as the independent variables. • We sort accruals or OCF into deciles each quarter, and assign each observation its decile rank (0 through 9). We then divide the rank by 9 and subtract 0.5. • The intercept in the regression is the mean future excess return. The slope coefficient is the excess return on a hedge portfolio with long positions in the most extreme negative accruals or positive OCF and short positions in the most positive accruals or negative OCF.

  37. Table 1. Summary Statistics on Rolling Four-Quarter Accruals and Cash-Flows

  38. Table 2. Regressions of Returns on Scaled Accrual Ranks and Scaled Cash Flows Ranks

  39. Table 3. Fama-MacBeth Regressions of Returns on Scaled Accrual Ranks and Scaled Cash Flows Ranks

  40. Table 4. Regressions of Next Quarter Returns on Scaled Rolling Four-Quarter Ranks by Fiscal Quarter

  41. Table 5. Regressions of Returns at Quarter t+4 on Scaled Rolling Four-Quarter Ranks by Fiscal Quarter

  42. Summary • OCF is uniformly superior to accruals, except for rolling four quarters and annual holding period in the fourth quarter. • This may shed some light on the inconsistency between Desai et al (2004) and further studies. Accruals seem to be incrementally valuation relevant for rolling four quarter data beyond OCF. They are particularly strong in the fourth fiscal quarter.

  43. Industry Analysis • Based on the 17 industries identified by Fama and French. • It uses 4-digit SIC codes to classify firms into industries. • Finer industries will have fewer observations for ranking accruals and OCF.

  44. Table 8. Regressions of Returns at Quarter t+4 on Scaled Rolling Four-Quarter Ranks by Industry

  45. Summary - Industry Analysis • Accruals are not a strong signal for most industries. OCF is a strong signal within all industries except one. • Accruals are not incrementally valuation relevant beyond OCF within any industry.

  46. Takeaways – Quarterly Accruals and OCF • Accruals are an inferior signal in predicting future returns to OCF. • The best case for accruals seems to be when they are based on rolling four quarters and and when the holding period id one year. • The only case for accruals to dominate OCF is for annual accruals and one-year holding period. • Accruals are inferior to OCF for within industry portfolio selection.

  47. Ronen Feldman Suresh Govindaraj Joshua Livnat Benjamin Segal The Incremental Information Content of Tone and Sentiment in Management Discussion and Analysis

  48. Overview • Can Investors learn from the tone of MD&A incremental information beyond the quantitative information? • Qualitative vs. quantitative information.

  49. Overview - Continued • Methodology: • Use classifications of words into “positive” and “negative”. • Determine the “tone” of an MD&A by the positive and negative word counts. • Examine short-window and drift returns associated with “tone” after controlling for earnings surprises and accruals.

More Related