Firms compete for reputational status in institutional fields. Managers attempt to influence other stakeholders' assessments by signaling firms' salient advantages. Stakeholders gauge firms' relati...

What's in a Name? Reputation Building and Corporate Strategy

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

https://sites.fas.harvard.edu/~ec970lt/Readings/March_14/Dechow%201994.pdf

Accounting earnings and cash flows as measures of firm performance: The role of accounting accruals

Previous research uses negative word counts to measure the tone of a text. We show that word lists developed for other disciplines misclassify common words in financial text. In a large sample of 10 Ks during 1994 to 2008, almost three-fourths of the words identified as negative by the widely used Harvard Dictionary are words typically not considered negative in financial contexts. We develop an alternative negative word list, along with five other word lists, that better reflect tone in financial text. We link the word lists to 10 K filing returns, trading volume, return volatility, fraud, material weakness, and unexpected earnings.

When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks

Previous research uses negative word counts to measure the tone of a text. We show that word lists developed for other disciplines misclassify common words in financial text. In a large sample of 10-Ks during 1994 to 2008, almost three-fourths of the words identified as negative by the widely used Harvard Dictionary are words typically not considered negative in financial contexts. We develop an alternative negative word list, along with five other word lists, that better reflect tone in financial text. We link the word lists to 10-K filing returns, trading volume, return volatility, fraud, material weakness, and unexpected earnings.

/pdf/when-is-a-liability-not-a-liability-textual-analysis-j5sx1r0swv.pdf

When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks

Post–earnings announcement drift is the tendency for a stock's cumulative abnormal returns to drift in the direction of an earnings surprise for several weeks following an earnings announcement. We show that the drift is significantly larger when defining the earnings surprise using analysts' forecasts and actual earnings from I/B/E/S than when using a time series model based on Compustat earnings data. Neither Compustat's policy of restating earnings nor the inclusion of “special items” in reported earnings contribute significantly to the disparity in drift magnitudes. Rather, our results suggest that this disparity is attributable to differences between analyst forecasts and those of time-series models—or at least to factors correlated with these differences. Further, we document that analyst forecasts lead to return patterns around future earnings announcements that differ from those observed when using time-series models, suggesting that the two types of surprises may capture somewhat different forms of mispricing.

Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts

This study explores whether the management discussion and analysis (MD&A) section of Forms 10-Q and 10-K has incremental information content beyond financial measures such as earnings surprises and accruals. It uses a classification scheme of words into positive and negative categories to measure the tone change in the MD&A section relative to prior periodic SEC filings. Our results indicate that short window market reactions around the SEC filing are significantly associated with the tone change of the MD&A section, even after controlling for accruals and earnings surprises. We show that management’s tone change adds significantly to portfolio drift returns in the window of 2 days after the SEC filing date through 1 day after the subsequent quarter’s preliminary earnings announcement, beyond financial information conveyed by accruals and earnings surprises. The drift returns are affected by the ability of the tone change signals to help predict the subsequent quarter’s earnings surprise but cannot be completely attributed to this ability. We also find that the incremental information of management’s tone change depends on the strength of the firm’s information environment.

/pdf/management-s-tone-change-post-earnings-announcement-drift-48vdoiaxi1.pdf

Management’s tone change, post earnings announcement drift and accruals

This study investigates investors' reactions to revenue and expense surprises around preliminary earnings announcements. Results show that investors value more highly a dollar of revenue surprise than a dollar of expense surprise. Results further show that these differential market reactions to revenue and expense surprises vary systematically for growth versus value firms and depend on (a) the proportion of variable to total costs, (b) the relative persistence of sales and expenses, and (c) the proportion of operating to total expenses. Results highlight the importance of interpreting the earnings surprise in the context of its sources—e.g. surprise in revenues or in total expenses.

Differential Market Reactions to Revenue and Expense Surprises

Two major diversification strategies of firms are examined: diversification into related businesses and diversification into unrelated businesses. The first strategy attempts to exploit operating synergies. In the second, the firm attempts to gain financial benefits from its ability to increase leverage due to a greater stability of cash flows.

The study utilizes a large sample affirms to assess empirically the benefits and costs of these two diversification strategies by developing a new measure of diversification across business cycles and economic sectors. This new measure is compared with Berry—Herfindahl type measures of total diversification and recent measures of diversification into related businesses.

The results indicate that pure financial diversification is associated with (a) more stable cash flows, i.e. lower operating risk; (b) increased levels of leverage; and (c) lower profitability. These observations are in accord with the theory. We also reaffirm that firms which diversify into related businesses have, on the average, higher profitability than non-diversified firms, although these results are not always statistically significant.

Diversification strategies, business cycles and economic performance

https://pages.stern.nyu.edu/~jlivnat/JAE%20submission.pdf

Joshua Livnat

Papers

Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts

Management’s tone change, post earnings announcement drift and accruals

Differential Market Reactions to Revenue and Expense Surprises

Diversification strategies, business cycles and economic performance

Revenue surprises and stock returns