MétaCan
Menu
Retour à la cohorte
Enregistrement W1483726685

Cautions Needed When Deciphering Firms' Quarterly Sales Patterns

2014· article· en· W1483726685 sur OpenAlexaboutno aff
Martin L. Gosman, Janice L. Ammons

Notice bibliographique

RevueAcademy of Accounting and Financial Studies journal · 2014
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueFinancial Reporting and Valuation Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésInterimFiscal yearCommissionQuarter (Canadian coin)BusinessRetail salesEconomicsAccountingMonetary economicsMarketingFinance
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

ABSTRACTTo make financial data timely, publicly-held firms must file interim reports on Form 10-Q in addition to their annual-reports (10-Ks) with Securities and Exchange Commission (SEC). In 10-Q filings, firms factor out any seasonality by comparing performance in current interim period and year-to-date with that of same time periods in prior fiscal year. However, because those studying a firm's performance are also interested in sales patterns within a given fiscal year, a table providing quarterly data for past two fiscal years is almost always presented in firms' 10-Ks. In this paper, quarterly sales patterns are first examined for Amazon, Macy's, Target, and Toys R Us, four firms expected to report their highest sales in fourth quarter because they feature merchandise known to sell especially well during end-of-year gift-giving season. Next, quarterly sales patterns are illustrated for three supermarkets and supplier of bread and pastry to supermarkets, firms that would expect to experience fairly even sales throughout year. Surprisingly, only of these firms reports a steady sales pattern. Each of other three firms reports interim period with sales at least 20 percent higher than all other periods. Equally noteworthy is fact that there is variety among three in whether their highest sales occur in first, third, or fourth interim period. The reason for these surprising findings among non-seasonal firms and implications for those examining firms' Forms 10-Q or their quarterly data in Forms 10-K are discussed. In addition, challenges faced by analysts attempting to compare a firm's quarterly sales trends with those of its peers or over time for same firm are illustrated by reference to quarterly-data disclosures of 15 additional companies.INTRODUCTIONTo better ensure availability of timely financial information to investors, creditors, and other users, Securities and Exchange Commission (SEC) requires that publicly-traded firms file interim-period reports on Form 10-Q, in addition to an annual report on Form 10-K. In contrast to 10-K data, 10-Q data need not be audited, but it must be reviewed by firm's independent auditor. The format used in reporting on Form 10-Q is designed to factor out any seasonal sales trends experienced by firm. Nevertheless, knowledge of seasonal trends and changes therein also are of interest to those studying a firm's results of operations. This latter information is typically presented in a firm's 10-K for all four quarters of two most recent years. Because this disclosure includes quarter-four results, firms are not required to file a separate Form 10-Q for their fourth quarter.Although some consider Q to be an abbreviation for one fourth of a (The Free Dictionary, 2013), SEC does not state that each 10-Q must cover an identical period of time (SEC, 1933-34, as amended). In an unofficial response to author, a researcher at SEC expressed view that a 13-week period is what most would associate with a quarter, but she noted that agency has not opined on number of weeks that should be included within each Form 10-Q.As will be illustrated, discretion afforded to firms has enabled reporting periods on Forms 10-Q that range from 12 to 17 weeks. This variability can present difficulties when analysts attempt to interpret a firm's seasonal trends and make inter-company (and even sometimes intra-company) comparisons. As a result, 10-Q disclosures must be viewed carefully since they could be misinterpreted by users who might assume that a firm's fiscal year would be divided into equal quarters for reporting on an SEC filing titled Form 10-Q. Given lack of specific guidance by SEC as to length of quarterly periods, AICPA in its guidance to auditors correctly notes that the term interim financial information means financial information or statements covering a period less than a full (AICPA, 2009). …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,065
score de la tête « metaresearch » (Gemma)0,314
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,065
Score d'incertitude au seuil0,345

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0650,314
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0090,011
Études des sciences et des technologies0,0020,002
Communication savante0,0080,005
Science ouverte0,0030,003
Intégrité de la recherche0,0010,004
Charge utile insuffisante (le modèle a refusé de juger)0,0040,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,059
Tête enseignante GPT0,320
Écart entre enseignants0,261 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueAcademy of Accounting and Financial Studies journalMême sujetFinancial Reporting and Valuation ResearchTravaux en français237 207