Professor Joshua Livnat, Ph.D., CPA
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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 [email protected] Web page: www.stern.nyu.edu/~jlivnat. The Standard & Poors’ Filing Dates Database – Research Applications. Overview.

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

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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

[email protected]

Web page: www.stern.nyu.edu/~jlivnat

The Standard & Poors’

Filing Dates Database –

Research Applications


Overview

Overview

  • The need for the database.

  • Description of the database.

  • Three research applications.


Data acknowledgements

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.


The market need

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.


The market need continued

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.


The market need continued1

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.


The s p filing dates database

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.


Digression the pit database

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.


Digression the pit database1

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.


Digression the pit database2

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.


Professor joshua livnat ph d cpa 10 76 k mec new york university 44 w 4th st ny ny 10012

The preliminary and

PIT databases


Matching gvkey cik

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.


Extracting sec data

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.


Professor joshua livnat ph d cpa 10 76 k mec new york university 44 w 4th st ny ny 10012

The S&P Filing Dates Database


Periodic reports

Periodic Reports


Proxy statements

Proxy Statements


Form 8 k

Form 8-K


Ford all filings

Ford – All Filings


Recent research applications

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.


Professor joshua livnat ph d cpa 10 76 k mec new york university 44 w 4th st ny ny 10012

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

[email protected]

German Lopez-Espinosa, University of Navarra

Rolling Quarterly Accruals and Cash

Flows: Universe and Industry Analysis


Overview1

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.


Overview continued

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.


Overview continued1

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.


Data acknowledgements1

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.


Definition accruals

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.


Professor joshua livnat ph d cpa 10 76 k mec new york university 44 w 4th st ny ny 10012

Sloan (1996) – Accrual Anomaly


Quarterly accruals

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.


Institutional considerations

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


Quarterly accruals research

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.


Accruals and ocf

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.


Open research questions

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?


Sample

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.


Variables

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).


Holding period

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.


Rolling four quarter data

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.


Analysis

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.


Table 1 summary statistics on rolling four quarter accruals and cash flows

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


Table 2 regressions of returns on scaled accrual ranks and scaled cash flows ranks

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


Table 3 fama macbeth regressions of returns on scaled accrual ranks and scaled cash flows ranks

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


Table 4 regressions of next quarter returns on scaled rolling four quarter ranks by fiscal quarter

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


Professor joshua livnat ph d cpa 10 76 k mec new york university 44 w 4th st ny ny 10012

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


Summary

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.


Industry analysis

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.


Table 8 regressions of returns at quarter t 4 on scaled rolling four quarter ranks by industry

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


Summary industry analysis

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.


Takeaways quarterly accruals and ocf

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.


Ronen feldman suresh govindaraj joshua livnat benjamin segal

Ronen Feldman

Suresh Govindaraj

Joshua Livnat

Benjamin Segal

The Incremental Information Content

of Tone and Sentiment in

Management Discussion and Analysis


Overview2

Overview

  • Can Investors learn from the tone of MD&A incremental information beyond the quantitative information?

  • Qualitative vs. quantitative information.


Overview continued2

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.


Overview continued3

Overview -Continued

  • Results:

    • The “tone” of MD&A has significant association with short-window abnormal returns around the SEC filing dates.

    • The “tone” has significant associations with drift returns even after controlling for earnings surprises and accruals.


Motivation

Motivation

  • Quantitative information such as earnings and accruals is associated with returns and drifts in returns. However, the associations are usually low.

  • Can qualitative information be incrementally beneficial for users beyond the quantitative information?.


Motivation continued

Motivation - Continued

  • There are several studies of qualitative information in articles written about firms and in preliminary earnings releases.

  • There may be self-selection in articles written about firms, because those may be induced by more significant “news”. Also, they do not capture management’s own “tone”.

  • Previous studies of earnings announcements did not include sufficiently large strings of releases.


Motivation continued1

Motivation - Continued

  • We study MD&A disclosures, which are available on a consistent basis four times a year.

  • Management is required to provide MD&A, unlike preliminary earnings releases.

  • The MD&A is subject to scrutiny by the SEC.

  • The SEC provided guidelines on what should be discussed in the MD&A.

  • The MD&A data are largely interpretive; past performance. It may include some future expectations.


Prior literature word counts

Prior Literature – Word Counts

  • Tetlock (2007) – “Abreast of the market”.

  • Tetlock et al (2008) – Articles about the S&P 500 constituents.

  • Engleberg (2008) – Earnings releases from Factiva.

  • Demers and Vega (2007) - Earnings releases. Diction 5.0.

  • Abrahamson and Amir (1996) - president’s letter.


Sample1

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.

  • Firms are on NYSE, AMEX or NASDAQ.

  • Q4/1995-Q2/2006.

  • Delete extreme 0.5% of returns on either side.

  • Over 170,000 firm-quarters.


Measuring tone

Measuring Tone

  • Use the General Inquirer dictionary of “positive’ and “negative” words.

  • Extracted the MD&A section. Counted the number of words (excluding numerical data), as well as the number of positive and negative words.

  • Computed the proportion of negative (positive) to total words, as well as

    (positive-negative)/(positive+negative).

  • Subtracted the mean measure in filings made within the previous 400 days to obtain a measure of tone shift.


Mean excess returns around sec filings for various signals

Mean Excess Returns around SEC Filings for Various Signals


Scaled ranks

Scaled Ranks

  • Sorted signals into quintiles.

  • Assigned the rank (0,4).

  • Divided by 4.

  • Subtracted -.5.

  • Slope regression coefficient can be interpreted as the hedge portfolio return of holding long (short) positions in the top (bottom) quintile.


Correlations among regression variables

Correlations among Regression Variables


Regression of short window returns on various signals

Regression of Short Window Returns on Various Signals


Mean excess drift returns for various signals

Mean Excess Drift Returns for Various Signals


Regression of drift excess returns on various signals

Regression of Drift Excess Returns on Various Signals


Mean hedge portfolio returns on various signals

Mean Hedge Portfolio Returns on Various Signals


Alina lerman joshua livnat

Alina Lerman

Joshua Livnat

The New Form 8-K Disclosures


Objective

Objective

  • New disclosure rules in 2004 about Form 8-K.

  • Some new items. Some expanded disclosure.

  • Shorter time to disclose (4 days).

  • How did it affect market reactions?

  • Are firms filing on time?


Methodology

Methodology

  • Examine immediate market reactions to the different categories of filing.

  • Examine abnormal volume and return volatility around filings.

  • Examine return drifts for the various categories.

  • Examine timeliness and its market reactions.


Sample in 2005 2006

Sample in 2005-2006


Abnormal returns 1 1

Abnormal Returns [-1,+1]


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