Asymptotics of Yule's nonsense correlation for Ornstein-Uhlenbeck paths: a Wiener chaos approach
arXiv:2108.02857
Abstract
In this paper, we study the distribution of the so-called "Yule's nonsense correlation statistic" on a time interval for a time horizon , when is large, for a pair of independent Ornstein-Uhlenbeck processes. This statistic is by definition equal to : \begin{equation*} ρ(T):=\frac{Y_{12}(T)}{\sqrt{Y_{11}(T)}\sqrt{Y_{22}(T)}}, \end{equation*} where the random variables , are defined as \begin{equation*} Y_{ij}(T):=\int_{0}^{T}X_{i}(u)X_{j}(u)du-T\bar{X}_{i}\bar{X_{j}}, \bar{X}_{i}:=\frac{1}{T}\int_{0}^{T}X_{i}(u)du. \end{equation*} We assume and have the same drift parameter . We also study the asymptotic law of a discrete-type version of , where above are replaced by their Riemann-sum discretizations. In this case, conditions are provided for how the discretization (in-fill) step relates to the long horizon . We establish identical normal asymptotics for standardized and its discrete-data version. The asymptotic variance of is . We also establish speeds of convergence in the Kolmogorov distance, which are of Berry-Esséen-type (constant*) except for a factor. Our method is to use the properties of Wiener-chaos variables, since and its discrete version are comprised of ratios involving three such variables in the 2nd Wiener chaos. This methodology accesses the Kolmogorov distance thanks to a relation which stems from the connection between the Malliavin calculus and Stein's method on Wiener space.