Self-normalized Cramér type moderate deviations for the maximum of sums

preprint2013arXivOpen access

Abstract

Let X1,X2,...X_1,X_2,... be independent random variables with zero means and finite variances, and let Sn=∑i=1nXiS_n=\sum_{i=1}^nX_i and Vn2=∑i=1nXi2V^2_n=\sum_{i=1}^nX^2_i. A Cramér type moderate deviation for the maximum of the self-normalized sums max⁡1≤k≤nSk/Vn\max_{1\leq k\leq n}S_k/V_n is obtained. In particular, for identically distributed X1,X2,...,X_1,X_2,..., it is proved that P(max⁡1≤k≤nSk≥xVn)/(1−Φ(x))→2P(\max_{1\leq k\leq n}S_k\geq xV_n)/(1-Φ(x))\rightarrow2 uniformly for 0<x≤o(n1/6)0<x\leq\mathrm{o}(n^{1/6}) under the optimal finite third moment of X1X_1.

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