Zachary R. Kaplan, Nathan T. Marshall, Jerry D. Mathis, Hanmeng Ivy Wang
{"title":"Forecasting Shares Outstanding","authors":"Zachary R. Kaplan, Nathan T. Marshall, Jerry D. Mathis, Hanmeng Ivy Wang","doi":"10.2139/ssrn.3837487","DOIUrl":null,"url":null,"abstract":"Despite the importance of EPS forecasts as benchmarks, little is known about their denominator: shares outstanding forecasts. Because investing clients have limited demand for accurate share forecasts, we predict that analysts develop share forecasts strategically to facilitate EPS incentives. We divide earnings forecasts by EPS forecasts to infer analysts’ share forecasts and evaluate their properties. Analysts’ forecasts of shares outstanding are significantly less accurate than simple time-series models; however, these same forecasts actually improve EPS forecast accuracy. Additional analysis explains why: analysts use share forecasts to herd EPS toward the consensus. That is, share forecast errors often have the same sign as street earnings forecast errors, moving EPS closer to the consensus and to actual EPS, and significantly reducing EPS dispersion. Analysts also appear to use share forecasts to cater to management. Specifically, bias in share forecasts facilitates firms’ ability to meet or beat (“MB”) EPS benchmarks and is consistent with manager preferences (i.e., deflating EPS forecasts at short horizons and inflating at longer horizons). Much of the MB effect arises because analysts fail to incorporate predictable variation in shares outstanding, such as past repurchases. Interviews with sell-side analysts confirm that clients have limited demand for share forecasts, consistent with the inattention and strategic use of forecasts documented in our study.","PeriodicalId":181062,"journal":{"name":"Corporate Governance: Disclosure","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Corporate Governance: Disclosure","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3837487","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Despite the importance of EPS forecasts as benchmarks, little is known about their denominator: shares outstanding forecasts. Because investing clients have limited demand for accurate share forecasts, we predict that analysts develop share forecasts strategically to facilitate EPS incentives. We divide earnings forecasts by EPS forecasts to infer analysts’ share forecasts and evaluate their properties. Analysts’ forecasts of shares outstanding are significantly less accurate than simple time-series models; however, these same forecasts actually improve EPS forecast accuracy. Additional analysis explains why: analysts use share forecasts to herd EPS toward the consensus. That is, share forecast errors often have the same sign as street earnings forecast errors, moving EPS closer to the consensus and to actual EPS, and significantly reducing EPS dispersion. Analysts also appear to use share forecasts to cater to management. Specifically, bias in share forecasts facilitates firms’ ability to meet or beat (“MB”) EPS benchmarks and is consistent with manager preferences (i.e., deflating EPS forecasts at short horizons and inflating at longer horizons). Much of the MB effect arises because analysts fail to incorporate predictable variation in shares outstanding, such as past repurchases. Interviews with sell-side analysts confirm that clients have limited demand for share forecasts, consistent with the inattention and strategic use of forecasts documented in our study.