A third-moment theorem and precise asymptotics for variations of stationary Gaussian sequences
Leo Neufcourt, Frederi Viens

TL;DR
This paper establishes a third-moment theorem for stationary Gaussian sequences, providing precise asymptotics for their variations and extending convergence results to non-Gaussian limits like the Rosenblatt law.
Contribution
It introduces a third-moment criterion for convergence of quadratic variations in Gaussian sequences and derives exact convergence speeds, extending prior fourth-moment results.
Findings
Third-moment theorem for Gaussian quadratic variations
Quantitative convergence speeds for non-Gaussian limits
Extension to log-modulated covariance structures
Abstract
In two new papers (Bierme et al., 2013) and (Nourdin and Peccati, 2015), sharp general quantitative bounds \ are given to complement the well-known fourth moment theorem of Nualart and Peccati, by which a sequence in a fixed Wiener chaos converges to a normal law if and only if its fourth cumulant converges to . The bounds show that the speed of convergence is precisely of order the maximum of the fourth cumulant and the absolute value of the third moment (cumulant). Specializing to the case of normalized centered quadratic variations for stationary Gaussian sequences, we show that a third moment theorem holds: convergence occurs if and only if the sequence's third moments tend to . This is proved for sequences with general decreasing covariance, by using the result of (Nourdin and Peccati, 2015), and finding the exact speed of convergence to of the quadratic variation's third…
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