Mean Squared Error (MSE)

Category: volatility

Calculates the Mean Squared Error (MSE) between two series over a rolling lookback window. It is commonly used to measure the fit of a moving average or to quantify volatility as the squared deviation from a mean.

Formula

MSE = \frac{1}{n} \sum_{i=0}^{n-1} (S1_{t-i} - S2_{t-i})^2

Inputs

• i_source1 (default: close)
• i_period (default: 100)

See signal primitives and every published strategy that uses Mean Squared Error (MSE) on WOBR StrategyVerse.