2018/07/12 by Wen-Chi Kuo, Kuo, Wen-Chi, Michael Rogans +5
Decision Sciences · Economics, Econometrics and Finance · Mathematics · #47B60 #60G20 #Advanced Banach Space Theory #FOS: Mathematics #Functional Analysis (math.FA) #Probability (math.PR) #Probability and Risk Models #Stochastic processes and financial applications #math.FA #math.PR #msc:47B60 #msc:60G20
paper · pdf · doi:10.48550/arxiv.1807.04869
arxiv created 2018/07/12 · openalex publication_date 2018/07/12 · arxiv updated 2018/07/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The abstraction of the study of stochastic processes to Banach lattices and vector lattices has received much attention by Grobler, Kuo, Labuschagne, Stoica, Troitsky and Watson over the past fifteen years. By contrast mixing processes have received very little attention. In particular mixingales were generalized to the Riesz space setting in \sc W.-C. Kuo, J.J. Vardy, B.A. Watson, Mixingales on Riesz spaces, \em J. Math. Anal. Appl., 402 (2013), 731-738. The concepts of strong and uniform mixing as well as related mixing inequalities were extended to this setting in \sc W.-C. Kuo, M.J. Rogans, B.A. Watson, Mixing inequalities in Riesz spaces, \em J. Math. Anal. Appl., 456 (2017), 992-1004. In the present work we formulate the concept of near-epoch dependence for Riesz space processes and show that if a process is near-epoch dependent and either strong or uniform mixing then the process is a mixingale, giving access to a law of large numbers. The above is applied to autoregessive processes of order 1 in Riesz spaces.