Disaggregating Operating and Financing Activities: Implications for Forecasts of Future Profitability

Esplin, Adam M.; Hewitt, Max; Plumlee, Marlene; Yohn, Teri Lombardi

doi:10.2139/ssrn.1543459

Cited by 10 publications

(5 citation statements)

References 21 publications

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“…First, estimating FULL using LAD yields smaller AFEs than any of the other models at any horizon. For example, the median AFE for one‐year horizon forecasts ranges from 0.051, or 5.1 percent (FULL LAD2 ) to 0.073, or 7.3 percent (AR); these values are consistent with prior research in ROE forecasting (e.g., Esplin, Hewitt, Plumlee, and Yohn report a median AFE of 0.079, or 7.9 percent, for their AR model of one‐year‐ahead ROE). Second, RW performs well vis‐à‐vis OLS models at short horizons, which suggests that OLS overweighs transitory items.…”

Section: Results On Statistical Significance Of Model‐based Forecastssupporting

confidence: 77%

An Examination of the Statistical Significance and Economic Relevance of Profitability and Earnings Forecasts from Models and Analysts

Evans

Njoroge

Yong

2017

Contemporary Accting Res

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In this paper, we propose and empirically test a cross-sectional profitability forecasting model which incorporates two major improvements relative to extant models. First, in terms of model construction, we incorporate mean reversion through the use of a twostage partial adjustment model and inclusion of a number of additional relevant determinants of profitability. Second, in terms of model estimation, we employ least absolute deviation (LAD) analysis instead of ordinary least squares because the former approach is able to better accommodate outliers. Results reveal that forecasts from our model are more accurate than three extant models at every forecast horizon considered and more accurate than consensus analyst forecasts at forecast horizons of two through five years. Further analysis reveals that LAD estimation provides the greatest incremental accuracy improvement followed by the inclusion of income subcomponents as predictor variables, and implementation of the two-stage partial adjustment model. In terms of economic relevance, we find that forecasts from our model are informative about future returns, incremental to forecasts from other models, analysts' forecasts, and standard risk factors. Overall, our results are important because they document the increased accuracy and economic relevance of a cross-sectional profitability forecasting model which incorporates improvements to extant models in terms of model construction and estimation.Les auteurs proposent et testent de fac ßon empirique un mod ele pr evisionnel de rentabilit e transversal comportant deux am eliorations importantes par rapport aux mod eles existants. En premier lieu, au chapitre de la structure du mod ele, les auteurs incorporent la r egression a la moyenne en utilisant un mod ele d'ajustement partiel a deux paliers et plusieurs d eterminants pertinents suppl ementaires de la rentabilit e. En second lieu, au chapitre de l'estimation du mod ele, les auteurs, plutôt que d'appliquer la m ethode classique des moindres carr es, ont recours a l'analyse du moindre ecart absolu parce qu'elle permet de mieux traiter les valeurs extrêmes. Ils constatent que les pr evisions produites par leur mod ele sont plus exactes que celles de trois mod eles existants, et cela pour tous les horizons pr evisionnels du plan de recherche, et qu'elles sont egalement plus exactes que les pr evisions consensuelles des analystes, pour les horizons pr evisionnels de deux a cinq ans. Une analyse plus pouss ee indique que l'estimation du moindre ecart absolu procure l'am elioration marginale la plus importante de l'exactitude, suivie de l'inclusion des sous-el ements du revenu a titre de variables ind ependantes et de l'emploi du mod ele d'ajustement partiel a deux paliers. Pour ce qui est de la pertinence economique, les auteurs observent que les pr evisions produites par leur mod ele sont plus r ev elatrices des rendements futurs que celles que fournissent les autres mod eles, que les pr evisions des analystes et que les facteurs de risque standard. Dans l'ensemble...

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Section: Results On Statistical Significance Of Model‐based Forecastssupporting

confidence: 77%

An Examination of the Statistical Significance and Economic Relevance of Profitability and Earnings Forecasts from Models and Analysts

Evans

Njoroge

Yong

2017

Contemporary Accting Res

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show abstract

“…Esplin et al . () find that the OPFIN model yields significantly less accurate forecasts than the aggregate ROE model but that the COMPONENT OPFIN model provides significantly more accurate forecasts than the aggregate ROE model. These findings provide guidance for fundamental analysis and suggest that the operating and financing disaggregation of profitability is only useful for forecasting when each component is forecasted separately and then combined to forecast ROE.…”

Section: Research On Fundamental Analysismentioning

confidence: 82%

“…This void in the literature led to Esplin et al . () which examines whether disaggregating operating and financing activities improves forecasts of ROE. Esplin et al .…”

Section: Research On Fundamental Analysismentioning

confidence: 99%

“…Esplin et al . () examine a base model that considers mean reversion in ROE (Eqn ) and an OPFIN model that disaggregates ROE into RNOA, NBC and LEV and allows a different coefficient on each component of ROE:

{ROE}_{t + 1} = α + β {RNOA}_{t} + β {NBC}_{t} + β {LEV}_{t} + ε_{t + 1} .

…”

Section: Research On Fundamental Analysismentioning

confidence: 99%

“…Esplin et al . () also examine a COMPONENT OPFIN model in which each component of ROE is estimated separately such that mean reversion in RNOA, mean reversion in NBC and mean reversion in LEV are estimated separately. The COMPONENT OPFIN model therefore forecasts RNOA, NBC and LEV separately before combining these forecasts to forecast year‐ahead ROE.…”

Section: Research On Fundamental Analysismentioning

confidence: 99%

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Research on the use of financial statement information for forecasting profitability

Yohn

2018

Accounting & Finance

Self Cite

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Research on the use of financial statement information for forecasting profitability has two objectives: (i) to generate improved forecasts of profitability and accurate estimates of firm value; and (ii) to identify market inefficiencies with respect to financial statement information. For these areas of research, this article describes the evolution, provides examples and shares implications of the research. It also discusses opportunities for future research. The article highlights that financial statement analysis research has slowly evolved and has received limited attention from academics. The article argues that there are vast opportunities for impactful research on fundamental analysis and market inefficiencies.

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The information content of disaggregated accounting profitability: operating activities versus financing activities

Lim

2013

Rev Quant Finan Acc

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Disaggregating Operating and Financing Activities: Implications for Forecasts of Future Profitability

Cited by 10 publications

References 21 publications

An Examination of the Statistical Significance and Economic Relevance of Profitability and Earnings Forecasts from Models and Analysts

An Examination of the Statistical Significance and Economic Relevance of Profitability and Earnings Forecasts from Models and Analysts

Research on the use of financial statement information for forecasting profitability

The information content of disaggregated accounting profitability: operating activities versus financing activities

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