Editing Forecasting (section)

==Limitations==

Limitations pose barriers beyond which forecasting methods cannot reliably predict. There are many events and values that cannot be forecast reliably. Events such as the roll of a die or the results of the lottery cannot be forecast because they are random events and there is no significant relationship in the data. When the factors that lead to what is being forecast are not known or well understood such as in [[Stock market|stock]] and [[foreign exchange market]]s forecasts are often inaccurate or wrong as there is not enough data about everything that affects these markets for the forecasts to be reliable, in addition the outcomes of the forecasts of these markets change the behavior of those involved in the market further reducing forecast accuracy.<ref name="https://www.otexts.org/fpp/1/1"/>

The concept of "self-destructing predictions" concerns the way in which some predictions can undermine themselves by influencing social behavior.<ref name=":0">{{Cite journal|last=Overland|first=Indra|date=2019-03-01|title=The geopolitics of renewable energy: Debunking four emerging myths|journal=Energy Research & Social Science|volume=49|pages=36–40|doi=10.1016/j.erss.2018.10.018|issn=2214-6296|doi-access=free|bibcode=2019ERSS...49...36O |hdl=11250/2579292|hdl-access=free}}</ref> This is because "predictors are part of the social context about which they are trying to make a prediction and may influence that context in the process".<ref name=":0" /> For example, a forecast that a large percentage of a population will become HIV infected based on existing trends may cause more people to avoid risky behavior and thus reduce the HIV infection rate, invalidating the forecast (which might have remained correct if it had not been publicly known). Or, a prediction that cybersecurity will become a major issue may cause organizations to implement more security cybersecurity measures, thus limiting the issue.

===Performance limits of fluid dynamics equations===
As proposed by [[Edward Lorenz]] in 1963, long range weather forecasts, those made at a range of two weeks or more, are impossible to definitively predict the state of the atmosphere, owing to the [[chaos theory|chaotic nature]] of the [[fluid dynamics]] equations involved. Extremely small errors in the initial input, such as temperatures and winds, within numerical models double every five days.<ref>{{cite book|title=Storm Watchers|pages=[https://archive.org/details/stormwatcherstur00cox_df1/page/222 222–224]|year=2002|author=Cox, John D.|publisher=John Wiley & Sons, Inc.|isbn=978-0-471-38108-2|url-access=registration|url=https://archive.org/details/stormwatcherstur00cox_df1/page/222}}</ref>