Central limit theorem for stationary linear processes

By Magda Peligrad, Sergey Utev. 2005

92 citations recorded by the source corpus.

We establish the central limit theorem for linear processes with dependent innovations including martingales and mixingale type of assumptions as defined in McLeish [Ann. Probab. 5 (1977) 616-621] and motivated by Gordin [Soviet Math. Dokl. 10 (1969) 1174-1176]. In doing so we shall preserve the generality of the coefficients, including the long range dependence case, and we shall express the variance of partial sums in a form easy to apply. Ergodicity is not required.

Subfields: Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/4e54c4dcd55e03fbcfaf117030a1cd9991e20ace

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. F. Merlevède
2. Magda Peligrad
3. Sergey Utev
4. Marek Tomasz Biskup
5. E. Rio
6. Wei Biao Wu
7. Michael H. Neumann

In Management Science and Operations Research

1. F. Merlevède
2. Magda Peligrad
3. Sergey Utev
4. Marek Tomasz Biskup
5. Wei Biao Wu
6. E. Rio
7. Michael H. Neumann

Citations in the corpus

• Recent progress on the Random Conductance Model (2011, background): “Another approach goes by imposing decay-rate conditions on time-correlations (e.g., Maxwell and Woodroofe [103], Derriennic and Lin [47], Peligrad and Utev [113], Klicnarová and Volný [88], Volný [133], etc.).”
• Recent advances in invariance principles for stationary sequences (2006, methodology): “and applying the martingale approximation method combined with the Bernstein blocking technique, Peligrad and Utev [56] proved the following central limit theorem, and further reaching results.”