Overfitting is a specific Trading coordinate in the Bitcoin knowledge graph. In practical terms, it identifies the subject described here: A strategy fitting historical noise so closely that apparent performance fails on new data. This definition is narrower than promotional usage and should be read together with the implementation, date and evidence attached to the entry.
Overfitting is best understood as part of a system rather than as an isolated definition. Its related coordinates show the mechanisms, incentives and historical records that give the term practical meaning.
Overfitting describes how participants value, trade or obtain exposure to bitcoin. Market behavior can affect adoption and mining economics, but it does not rewrite consensus rules. Price evidence and protocol evidence answer different questions.
Understanding Overfitting helps distinguish a verifiable Bitcoin mechanism or historical record from slogans, products and market narratives.
Backtest overfitting occurs when repeated model, rule or parameter searches select a strategy that explains noise in one historical sample. The reported winner inherits selection bias from every failed trial; untouched out-of-sample testing, trial counts, realistic costs and stability checks are therefore part of the evidence, not optional polish.
Primary records expose these checkable anchors: many trials + one historical sample → selection bias · PBO framework · untouched out-of-sample · costs and parameter stability. Dates, roles, formulas and institutional actions should be verified there before interpretation.
The safe boundary is: in-sample performance ≠ independent evidence; one holdout repeatedly consulted ≠ untouched test; Sharpe ratio ≠ proof after selection. The coordinate records evidence and mechanism; it does not turn advocacy, correlation or a model output into a Bitcoin consensus fact.
For the clearest picture, read this entry together with Backtesting, Walk-forward analysis, Look-ahead bias, Survivorship bias. The reverse links also lead from Technical analysis, Technical indicator, Divergence, Backtesting.