• Title/Summary/Keyword: Chaining argument

Search Result 3, Processing Time 0.019 seconds

A Uniform CLT for Continuous Martingales

  • Bae, Jong-Sig;Shlomo Leventatl
    • Journal of the Korean Statistical Society
    • /
    • v.24 no.1
    • /
    • pp.225-231
    • /
    • 1995
  • An eventual uniform equicontinuity condition is investigated in the context of the uniform central limit theorem (UCLT) for continuous martingales. We assume the usual intergrability condition on metric entropy. We establish an exponential inequality for a martingales. Then we use the chaining lemma of Pollard (1984) to prove an eventual uniform equicontinuity which is a sufficient condition of UCLT. We apply the result to approximate a stochastic integral with respect to a martingale to that of a Brownian motion.

  • PDF

THE SECOND CENTRAL LIMIT THEOREM FOR MARTINGALE DIFFERENCE ARRAYS

  • Bae, Jongsig;Jun, Doobae;Levental, Shlomo
    • Bulletin of the Korean Mathematical Society
    • /
    • v.51 no.2
    • /
    • pp.317-328
    • /
    • 2014
  • In Bae et al. [2], we have considered the uniform CLT for the martingale difference arrays under the uniformly integrable entropy. In this paper, we prove the same problem under the bracketing entropy condition. The proofs are based on Freedman inequality combined with a chaining argument that utilizes majorizing measures. The results of present paper generalize those for a sequence of stationary martingale differences. The results also generalize independent problems.

THE LIMITING LOG GAUSSIANITY FOR AN EVOLVING BINOMIAL RANDOM FIELD

  • Kim, Sung-Yeun;Kim, Won-Bae;Bae, Jong-Sig
    • Communications of the Korean Mathematical Society
    • /
    • v.25 no.2
    • /
    • pp.291-301
    • /
    • 2010
  • This paper consists of two main parts. Firstly, we introduce an evolving binomial process from a binomial stock model and consider various types of limiting behavior of the logarithm of the evolving binomial process. Among others we find that the logarithm of the binomial process converges weakly to a Gaussian process. Secondly, we provide new approaches for proving the limit theorems for an integral process motivated by the evolving binomial process. We provide a new proof for the uniform strong LLN for the integral process. We also provide a simple proof of the functional CLT by using a restriction of Bernstein inequality and a restricted chaining argument. We apply the functional CLT to derive the LIL for the IID random variables from that for Gaussian.