English

Persistence of iterated partial sums

Probability 2015-06-05 v1

Abstract

Let Sn(2)S_n^{(2)} denote the iterated partial sums. That is, Sn(2)=S1+S2+...+SnS_n^{(2)}=S_1+S_2+ ... +S_n, where Si=X1+X2+...s+XiS_i=X_1+X_2+ ... s+X_i. Assuming X1,X2,....,XnX_1, X_2,....,X_n are integrable, zero-mean, i.i.d. random variables, we show that the persistence probabilities pn(2):=\PP(max1inSi(2)<0)c\EESn+1(n+1)\EEX1,p_n^{(2)}:=\PP(\max_{1\le i \le n}S_i^{(2)}< 0) \le c\sqrt{\frac{\EE|S_{n+1}|}{(n+1)\EE|X_1|}}, with c630c \le 6 \sqrt{30} (and c=2c=2 whenever X1X_1 is symmetric). The converse inequality holds whenever the non-zero min(X1,0)\min(-X_1,0) is bounded or when it has only finite third moment and in addition X1X_1 is squared integrable. Furthermore, pn(2)n1/4p_n^{(2)}\asymp n^{-1/4} for any non-degenerate squared integrable, i.i.d., zero-mean XiX_i. In contrast, we show that for any 0<γ<1/40 < \gamma < 1/4 there exist integrable, zero-mean random variables for which the rate of decay of pn(2)p_n^{(2)} is nγn^{-\gamma}.

Keywords

Cite

@article{arxiv.1205.5596,
  title  = {Persistence of iterated partial sums},
  author = {Amir Dembo and Jian Ding and Fuchang Gao},
  journal= {arXiv preprint arXiv:1205.5596},
  year   = {2015}
}

Comments

overlaps and improves upon an earlier version by Dembo and Gao at arXiv:1101.5743

R2 v1 2026-06-21T21:09:18.789Z