Editing Forecasting (section)

===Qualitative vs. quantitative methods===

Qualitative forecasting techniques are subjective, based on the opinion and judgment of consumers and experts; they are appropriate when past data are not available.
They are usually applied to intermediate- or long-range decisions. Examples of qualitative forecasting methods are{{citation needed|date=May 2012}} informed opinion and judgment, the [[Delphi method]], [[market research]], and historical life-cycle analogy.

Quantitative forecasting [[mathematical model|models]] are used to forecast future data as a function of past data. They are appropriate to use when past numerical data is available and when it is reasonable to assume that some of the patterns in the data are expected to continue into the future.
These methods are usually applied to short- or intermediate-range decisions. Examples of quantitative forecasting methods are{{citation needed|date=May 2012}} last period demand, simple and weighted N-Period [[moving average]]s, simple [[exponential smoothing]], Poisson process model based forecasting<ref>{{cite conference |title= A poisson process model for activity forecasting |last1= Mahmud |first1= Tahmida |last2= Hasan |first2= Mahmudul |last3= Chakraborty |first3= Anirban |last4= Roy-Chowdhury |first4= Amit |date= 19 August 2016 |publisher= IEEE |conference= 2016 IEEE International Conference on Image Processing (ICIP) |doi= 10.1109/ICIP.2016.7532978 }}</ref> and multiplicative seasonal indexes. Previous research shows that different methods may lead to different level of forecasting accuracy. For example, [[Group method of data handling|GMDH]] neural network was found to have  better forecasting performance than the classical forecasting algorithms such as Single Exponential Smooth, Double Exponential Smooth, ARIMA and back-propagation neural network.<ref>{{Cite journal | doi=10.1080/14445921.2016.1225149|title = Forecasting the REITs and stock indices: Group Method of Data Handling Neural Network approach| journal=Pacific Rim Property Research Journal| volume=23| issue=2| pages=123–160|year = 2017|last1 = Li|first1 = Rita Yi Man| last2=Fong| first2=Simon| last3=Chong| first3=Kyle Weng Sang|s2cid = 157150897}}</ref>