Judgmental Forecasting. Three components of a time series influence the degree of difficultythat is associated withthe judgmental forecasting task, namely:· the complexityof the underlying signal, comprising factors such as itsseasonality,cyclesandtrends,and autocorrelation;:thelevel of noisearoundthesignal; and: the stability of the underlying signal.Commonmistakes·Damping thetrend: Confusing noise with signal:Underestimationofuncertainty
Judgmental Forecasting • Three components of a time series influence the degree of difficulty that is associated with the judgmental forecasting task, namely: • the complexity of the underlying signal, comprising factors such as its seasonality, cycles and trends, and autocorrelation; • the level of noise around the signal; and • the stability of the underlying signal. • Common mistakes • Damping the trend • Confusing noise with signal • Underestimation of uncertainty
? Skill Score(MSEy)(H)E(Yi- 0,)MSEs= (H)(0- 0.)2SS=1MSEy=MSEB: Murphy's decomposition (Murphy, 1988)ss=(ro)-[ro-(]"-{-]where rxo is thecorrelation between theforecast and the observed event;sy and so are thestandard deviations of the forecast and the observed event, respectively; and Y and O are themeans of theforecastandtheobserved event.Murphycalledthesecondterm'conditionalbias.Murphycalledthethirdterm‘unconditionalbias
• Skill Score • Murphy’s decomposition (Murphy, 1988)
·3-stepdecomposition(Steward&Lusk,1994):Step1-Murphy'sdecomposition:Step2-Usethelensmodel equation (LME)tofurtherdecomposethecorrelationcomponentoftheMurphy'sdecomposition.TheLMEshowsthatthecorrelationisdeterminedbypropertiesoftheenvironmentalsystem,thecognitivesystemandtherelationsbetweenthem.·Step3-Thetwocomponents(unreliabilityofsubjectiveinterpretationofcues and unreliability of information processing)are further decomposed
• 3-step decomposition (Steward & Lusk, 1994) • Step 1 – Murphy’s decomposition • Step 2 - Use the lens model equation (LME) to further decompose the correlation component of the Murphy’s decomposition. The LME shows that the correlation is determined by properties of the environmental system, the cognitive system and the relations between them. • Step 3 – The two components (unreliability of subjective interpretation of cues and unreliability of information processing) are further decomposed
SS=Skil Score=1-(MSE/MSE,)ConditionalUnconditionalSquaredcomelation(regression)(base rate)biasbiasStep 1:(rmo)"SS=Murphy[0 -(5v/80)]"-[(Y-0)/s0]?(1988)Step 2:GSSi(RoxRyx)Tucker[ro-(sy1s0)[(Y.0)1s0](1964)Step3:ExpandedRu)"- [vo -($1s0)]"-[(Y.0)/s0]?VixGVuxSSE(Rotlensmodel0?OOOO①Components of skill:1.Environmentalpredictabity2.Fidellty of theinfomation system3.Matchbetweenenvironnentandforecaster4.Reliabilityofinfomationacquisition5.Reliabilityof infomationprocessing6.Conditiona/regressionbias7.Unconditional/base ratebias
Table I.Components of skill addressed by selected methods for improving forecastsComponent of skill"-23456MethodforimprovingforecastsxAIdentifynewdescriptorsthroughresearchxBDevelopbettermeasuresoftruedescriptorsxxxxcTrainforecasteraboutenvironmental systemxXDExperiencewithforecastingproblemECognitivefeedbackFTrainforecastertoignorenon-predictivecuesXXXGDevelopcleardefinitionsof cuesHTraining to improve cue judgmentsx1ImproveinformationdisplaysXxxxxJBootstrapping-replaceforecaster with modelKCombine several forecastsxLRequire justification of forecastsMDecomposeforecastingtaskNMechanical combination of cuesXxxxX0Statistical trainingPxFeedback about nature of biases in forecastQSearch fordiscrepant informationxRStatistical correction for bias