Estimating the Half-Life of Mean Reversion with an Ornstein-Uhlenbeck Model

Summary

This documentation describes a function for estimating the half-life of a mean-reverting process under an Ornstein-Uhlenbeck assumption. The model represents changes in a variable as a pull toward a level, plus Gaussian noise. The half-life is a way to characterize how quickly deviations are expected to decay, which can help assess the speed of reversion in a spread.

The page identifies a utility function and shows it being applied to a spread series, but gives no derivation, parameter-estimation details, sample data, or performance evidence. The estimate depends on the Ornstein-Uhlenbeck model being a reasonable description of the data; the document does not discuss uncertainty or diagnostics for that assumption. It is a brief software reference rather than a full treatment of mean-reversion strategy design.

Key ideas

• The function estimates mean-reversion half-life assuming an Ornstein-Uhlenbeck process.
• The model describes a variable reverting toward a level while being affected by Gaussian noise.
• A spread series is given as the function's example input.
• The page does not explain estimation details, provide validation, or discuss model diagnostics.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.