Definitions
The core vocabulary of forecastability. These definitions are stable and permanently anchor-linked for citation.
Forecastability. The amount of predictive information the observed past of a process carries about its future at a given horizon. It is a property of the series and the horizon, not of any model. High forecastability means the future is substantially knowable from the past; low forecastability means it is not, whatever method is applied.
Forecastability profile, F(h). The function mapping each forecast horizon h to the predictive information available at that horizon. The profile is the complete, model-independent statement of how knowable a series’ future is, and the ceiling against which any method’s performance should be read.
Exploitability. The predictive information a given method actually converts into realised performance at a horizon. Where forecastability is a property of the series, exploitability is a property of the method, evaluable only after modelling. Its ceiling at every horizon is F(h).
The exploitability ceiling. The horizon-specific limit that F(h) places on the exploitability of any forecasting method using the same information set. Methods can approach the ceiling; none can exceed it.
Exploitability gap. The distance between the ceiling and a method’s exploitability at a given horizon: information that was available and went unexploited. The gap is the honest measure of forecasting performance.
Exploitability ratio. Exploitability as a share of the ceiling: the fraction of available predictive information a method converts into realised performance, comparable across series, horizons and methods.
Entropy. The information-theoretic measure of uncertainty: the average information required to specify an outcome. It is maximal for pure noise, lower wherever structure constrains what happens next, and the baseline a forecast is trying to reduce.
Auto-mutual information, AMI. The mutual information between a series’ past and its value h steps ahead: the predictive information the past actually carries at each horizon. Read across horizons it yields the forecastability profile; it is how forecastability is measured in practice.
Predictive information decay. The characteristic decline of F(h) as the horizon lengthens. Decay rates differ across processes and domains, which is why the same method can excel at one horizon and fail at another.
Forecast triage. The allocation of modelling effort according to measured forecastability: sophisticated methods where information is rich, simple baselines where it is thin, and decision design where it is absent.
Predictive decision authority. The principle that the operational authority granted to a predictive system should scale with the forecastability of its domain. Systems forecasting weakly knowable processes should advise; only systems forecasting strongly knowable processes should act.
Cite this page: Catt, P.M. (2026). Definitions. The Knowable Future. theknowablefuture.com/definitions