會(huì)計(jì)數(shù)據(jù)分析 課件 第8章　財(cái)務(wù)報(bào)表分析

FinancialStatementAnalyticsChapter8Wherewearenow1.DataAnalytics2.DataPreparationandCleaning3.ModelingandEvaluation4.Visualization5.TheModernAudit6.AuditAnalytics7.KeyPerformanceIndicators8.FinancialStatementAnalyticsObjectivesLO8-1DescribehowXBRLtagsfinancialreportingdataLO8-2UnderstandhowdifferenttypesofratioanalysiscanbefacilitatedbyXBRLLO8-3ExplainhowtocreateandreadvisualizationsoffinancialstatementdataLO8-4DescribethevalueoftextminingandsentimentanalysisoffinancialreportingHowdoesXBRLwork?LO8-1XBRLstandsforeXtensibleBusinessReportingLanguageandisatypeofXML(extensiblemarkuplanguage)usedfororganizinganddefiningfinancialelements.Theuseoftagsallowsdatatobequicklytransmittedandreceived,andthetagsserveasaninputforanalyticsmodelsusedbyfinancialanalysts,auditors,orregulators.AsofJune2011,theSECrequirestaggingof:NumbersandDatesBalancesheetIncomestatementStatementofcomprehensiveincomeStatementofcashflowsStatementofstockholders’equityTextBlocks,includingNumbersandDatesFootnotesManagementdiscussionandanalysis(MD&A)Eachdataelementistaggedtoidentifywhattheyare(e.g.cash)andcontext(e.g.USdollars,2014Q4)inaninstancedocument.Forexample,thiselementrepresentsthecashandcashequivalentsbalanceonthebalancesheetattheendofquarter4of2014.ItwouldberoundedtothethousandofUSdollars.TagfromUSGAAPTaxonomy

Contexttaganduniqueidentifier

Presentationandcurrency

FACT

Endoftag<us-gaap:CashAndCashEquivalentsAtCarryingValue

contextRef="FI2014Q4"

id="Fact-2FCE60A0E1BB610AF2F1292924554784"

unitRef="iso4217_USD"

decimals="-3">

667593000

</us-gaap:CashAndCashEquivalentsAtCarryingValue>AnalysisofXBRLdatacanbedifficultbecausedifferentcompaniesmayusedifferenttags.

Forexampletoshowtotalrevenue,IBMusestheRevenuestagandAppleusesSalesRevenueNet.XBRLanalyticalsoftwareusesstandardizedmetricstoconsolidatesimilartags(e.g.bothRevenuesandSalesRevenuesNetappearinastandard[Revenue]metric.)Currentlyfinancialstatementsaretaggedmanuallyattheendoftheperiod.Inthefuture,XBRL-GLmaybeappliedtoindividualtransactionstofacilitatereal-timereporting.Q.HowmightstandardizedXBRLmetricsbeusefulincomparingthefinancialstatementsofGeneralMotors,Alphabet,andAlibaba?HowdoesXBRLenableratioanalysis?LO8-2Financialstatementanalysisisusedbyinvestors,analysts,auditors,andotherinterestedstakeholderstoreviewandevaluateacompany’sfinancialstatementsandfinancialperformance.Ratioanalysisisatoolusedtoevaluaterelationshipsamongdifferentfinancialstatementitemstoassessthefinancialhealthofabusiness.Therearebasicallyfourtypesofratios:Liquidityistheabilitytosatisfythecompany’sshort-termobligations(e.g.currentandacid-test)Activityratiosareacomputationofafirm’soperatingefficiency(e.g.assetturnover)Solvency(orfinancing)ratioshelpassessacompany’sabilitytopayitsdebtsandstayinbusiness(e.g.debt-to-equity)Profitabilityratiosprovideinformationontheprofitabilityofacompanyanditsprospectsforthefuture(e.g.profitmargin)TheDuPontratiomeasurescomponentsofreturnonequity.Returnonequity(ROE)=Profitmargin×Assetturnover×Financialleverage=(Netprofit/Sales)×(Sales/Averagetotalassets)×(Averagetotalassets/Averageequity)Forexample,DuPont’s2009Q2returnonequityis27.8%

=29.4%PMx20.1%ATx471.7%FLQ.Whatarethecomponentsofprofitmargin,operatingleverageandfinancialleverage?Howcanyoucreatesimplefinancialstatementvisualizations?LO8-3Sparklinesaresmallgraphictrendlinesthatefficientlysummarizesnumbersorstatisticsinagraphwithoutaxesinasinglespreadsheetcell.Sparklinesareusefulforcreatingsimpledashboardsorsummarizinglargesheetofnumbers.Exhibit8-4Sparklines(left)showthetrendsintheDuPontanalysisQ.HowmightsparklinesbeusedtoenhanceaDuPontanalysis?Wouldyoushowthesparklinesforeachcomponentoftheratio,orwouldyouproposeitbeshownonlyforthetotal?Howdoestextminingandsentimentanalysiswork?LO8-4Textmininganalyzesthefrequencyofwordsinunstructureddata(e.g.financialdisclosure)andmatchesthosetoasentimentdictionary(e.g.wordsidentifiedaspositiveornegative).Forfinancialstatements,theLoughranandMcDonalddictionarycancategorizewordsbysentiment:Positive(e.g.enable,achieve)Negative(e.g.loss,adverse)Uncertain(e.g.anticipate,depend)Litigious(e.g.mediate,petition)Modal(e.g.possible,likely)Constraining(e.g.commit,impair)Theproportionofaclassofwordscanbeusefulinpredictinginvestmentreturns.Onestudyshowsthatthehighertheproportionofnegativewordsin10-Kdisclosure,thelowerthereturns.Thesolidlineshowsafinancialdictionary,andthedashedlineshowsanormalEnglishdictionarywithnegativewordclassifications.Exhibit8-5Stockmarketreactionrelativetoproportionofnegativeworks(2011,LoughranandMcDonald)Analystscantracksentimentproportionovertimeandanalyzeothertextsources(e.g.newsarticles,socialmedia)torealizegainsinthemarket.Q.Whichwouldyoupredictwouldhavemorepositivesentimentina10-K?

A.Thefootnotestothefinancialstatements

B.TheMD&AsectionofthefinancialstatementsSummary