Sample size
Sample size is the number of independent trades or observations behind a result. The fewer there are, the more a result can be luck.
How Sample size is calculated
The uncertainty of an average shrinks with the square root of the number of observations. A win rate measured on 25 trades could easily be 15 points away from the true rate. Trades that overlap in time or move together carry less information than the raw count suggests, so seasonal rules with one signal a year have very small samples.
How it is read
A common rule of thumb is to want at least a few dozen independent trades before reading anything into an average. More is better.
Common mistakes
- Counting bars or days as trades.
- Quoting a percent from 10 trades.
- Forgetting that a result found by searching needs a bigger sample than one set in advance.
What Tickfloor tested
Tickfloor has not published a backtest of a rule built only on Sample size. It describes or manages something rather than giving a signal, so there is no strategy to score. It still shapes how any tested rule should be read.
Lessons that cover it
- Seasonality: calendar effects that shrink once people know
- What the research says about active traders, and what overtrading costs
- Reviewing your journal with numbers
Related concepts
General information only. It doesn't consider your objectives, finances or needs. Tickfloor holds no financial services licence and never places trades.