Editing Forecasting (section)

== Applications ==
Forecasting has applications in a wide range of fields where estimates of future conditions are useful. Depending on the field, accuracy varies significantly. If the factors that relate to what is being forecast are known and well understood and there is a significant amount of data that can be used, it is likely the final value will be close to the forecast. If this is not the case or if the actual outcome is affected by the forecasts, the reliability of the forecasts can be significantly lower.<ref name="https://www.otexts.org/fpp/1/1">{{Cite book|url=https://www.otexts.org/fpp/1/1|title=Forecasting: Principles and Practice}}</ref> 

Climate change and increasing energy prices have led to the use of [[Egain Forecasting]] for buildings. This attempts to reduce the energy needed to heat the building, thus reducing the emission of [[greenhouse gas]]es. Forecasting is used in [[customer demand planning]] in everyday business for manufacturing and distribution companies.

While the veracity of predictions for actual stock returns are disputed through reference to the [[efficient-market hypothesis]], [[Economic forecasting|forecasting of broad economic trends]] is common. Such analysis is provided by both non-profit groups as well as by for-profit private institutions.{{citation needed|date=January 2019}}

Forecasting [[exchange rate|foreign exchange]] movements is typically achieved through a combination of historical and current data (summarized in charts) and [[fundamental analysis]]. An essential difference between chart analysis and fundamental economic analysis is that chartists study only the price action of a market, whereas fundamentalists attempt to look to the reasons behind the action.<ref>{{cite journal|author1=Helen Allen|author2=Mark P. Taylor|year=1990|title=Charts, Noise and Fundamentals in the London Foreign Exchange Market|journal=The Economic Journal|volume=100|issue=400|pages=49–59|doi=10.2307/2234183|jstor=2234183}}</ref> Financial institutions assimilate the evidence provided by their fundamental and chartist researchers into one note to provide a final projection on the currency in question.<ref name="InstutionalResearch">Pound Sterling Live. [https://www.poundsterlinglive.com/euroforecast "Euro Forecast from Institutional Researchers"], A list of collated exchange rate forecasts encompassing technical and fundamental analysis in the foreign exchange market.</ref>

Forecasting has also been used to predict the development of conflict situations.<ref>T. Chadefaux (2014). "Early warning signals for war in the news". Journal of Peace Research, 51(1), 5-18	</ref> Forecasters perform research that uses empirical results to gauge the effectiveness of certain forecasting models.<ref name=faq>{{cite web|author1=J. Scott Armstrong|author2=Kesten C. Green|author3=Andreas Graefe|year=2010|title=Answers to Frequently Asked Questions|url=http://qbox.wharton.upenn.edu/documents/mktg/research/FAQ.pdf|url-status=dead|archive-url=https://web.archive.org/web/20120711003404/http://qbox.wharton.upenn.edu/documents/mktg/research/FAQ.pdf|archive-date=2012-07-11|access-date=2012-01-23}}</ref> However research has shown that there is little difference between the accuracy of the forecasts of experts knowledgeable in the conflict situation and those by individuals who knew much less.<ref>{{cite journal|author1=Kesten C. Greene|author2=J. Scott Armstrong|year=2007|title=The Ombudsman: Value of Expertise for Forecasting Decisions in Conflicts|url=http://marketing.wharton.upenn.edu/documents/research/Value%20of%20expertise.pdf|url-status=dead|journal=Interfaces|pages=1–12|archive-url=https://web.archive.org/web/20100620223405/http://marketing.wharton.upenn.edu/documents/research/Value%20of%20expertise.pdf|archive-date=2010-06-20|access-date=2011-12-29}}</ref> Similarly, experts in some studies argue that role thinking — standing in other people's shoes to forecast their decisions — does not contribute to the accuracy of the forecast.<ref>{{cite journal|author1=Kesten C. Green|author2=J. Scott Armstrong|year=1975|title=Role thinking: Standing in other people's shoes to forecast decisions in conflicts|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1596623|journal=International Journal of Forecasting |volume=39|pages=111–116|ssrn=1596623 }}</ref> 

An important, albeit often ignored aspect of forecasting, is the relationship it holds with [[planning]]. Forecasting can be described as predicting what the future ''will'' look like, whereas planning predicts what the future ''should'' look like.<ref name=faq /> There is no single right forecasting method to use. Selection of a method should be based on your objectives and your conditions (data etc.).<ref>{{cite web|date=1998-02-14|title=FAQ|url=http://www.forecastingprinciples.com/index.php?option=com_content&task=view&id=3&Itemid=3#D._Choosing_the_best_method|archive-url=https://archive.today/20130124070128/http://www.forecastingprinciples.com/index.php?option=com_content&task=view&id=3&Itemid=3%23D._Choosing_the_best_method|url-status=dead|archive-date=January 24, 2013|access-date=2012-08-28|publisher=Forecastingprinciples.com}}</ref> A good way to find a method is by visiting a selection tree. An example of a selection tree can be found here.<ref>{{cite web|date=1998-02-14|title=Selection Tree|url=http://www.forecastingprinciples.com/index.php?option=com_content&task=view&id=17&Itemid=17|archive-url=https://web.archive.org/web/20090415193625/http://www.forecastingprinciples.com/index.php?option=com_content&task=view&id=17&Itemid=17|url-status=dead|archive-date=April 15, 2009|access-date=2012-08-28|publisher=Forecastingprinciples.com}}</ref>

Forecasting has application in many situations:
*[[Supply chain management]] and [[customer demand planning]] — Forecasting can be used in supply chain management to ensure that the right product is at the right place at the right time. Accurate forecasting will help retailers reduce excess inventory and thus increase [[profit margin]]. Accurate forecasting will also help them meet consumer demand. The discipline of demand planning, also sometimes referred to as supply chain forecasting, embraces both statistical forecasting and a consensus process. Studies have shown that extrapolations are the least accurate, while company earnings forecasts are the most reliable.{{clarify|date=December 2013}}<ref>{{cite journal|author=J. Scott Armstrong|year=1983|title=Relative Accuracy of Judgmental and Extrapolative Methods in Forecasting Annual Earnings|url=http://www.forecastingprinciples.com/paperpdf/Monetary%20Incentives.pdf|journal=Journal of Forecasting|volume=2|issue=4|pages=437–447|doi=10.1002/for.3980020411|s2cid=16462529}}</ref>  
*[[Economic forecasting]]
*[[Earthquake prediction]]
*[[Egain forecasting]]
*[[Energy forecasting]] for renewable power integration
*[[Finance]] against risk of [[default (finance)|default]] via [[credit rating]]s and [[credit score]]s
*[[Land use forecasting]]
*[[PECOTA|Player and team performance in sports]]
*[[Political forecasting]]
*[[Product forecasting]]
*[[Sales forecasting]]
*[[Technology forecasting]]
*[[Telecommunications forecasting]]
*[[Transport planning]] and [[transportation forecasting|forecasting]]
*[[Weather forecasting]], [[flood forecasting]] and [[meteorology]]