Characterization of degenerate scaling

This post is a follow-up to my post on 12/29/2023, where I posed the following question:

Let (X_n) be an i.i.d. sequence of \mathbb{R}-valued random variables. Let (a_n) be a positive sequence such that \lim a_n=\infty. Under what condition of (a_n) can one conclude that \lim\frac{X_n}{a_n}=0 almost surely?

I have found a full characterization of the sequence (a_n). After all, it is an interesting exercise.

Proposition: Let (X_n) be an i.i.d. sequence of \mathbb{R}-valued random variables Let (a_n) be a positive sequence such that \lim a_n=\infty. If \sum P\left(|X_1|>\frac{a_n}{c}\right)<\infty for any constant c>0, then \lim\frac{X_n}{a_n}=0 almost surely. Otherwise, almost surely \frac{X_n}{a_n} does not converge.

As an application, if (X_n) is an i.i.d. sequence of mean-one exponentially distributed random variables, then almost surely the sequence of \frac{X_n}{\ln n} does not converge.

Proof: First, suppose that there exists c>0 such that \sum P\left(|X_1|>\frac{a_n}{c}\right)=\infty. Then the independent events E_n=[|X_n|>\frac{a_n}{c}] satisfies

\displaystyle \sum \mathbb{P}(E_n)=\infty.

By Borel-Cantelli’s Lemma, almost surely the events E_n occurs for infinitely many n. Therefore, with probability 1, the sequence (X_n/a_n) does not converge to 0. Now fix b\neq 0. We show that almost surely X_n/a_n\not\to b. Consider the independent events E'_n=\left[|X_n|<\frac{|b|a_n}{2}\right]. One has

\displaystyle \sum\mathbb{P}(E'_n)=\infty

By Borel-Cantelli’s Lemma, almost surely the events E'_n occurs for infinitely many n. Therefore, with probability 1, the sequence (X_n/a_n) does not converge to b.

Next, suppose that for every c>0, one has \sum P\left(|X_1|>\frac{a_n}{c}\right)<\infty. For a fixed constant c>0, the event A_c=\left[\limsup\frac{|X_n|}{a_n}\le \frac{1}{c}\right] is a tail event. Thus, \mathbb{P}(A_c)=0 or \mathbb{P}(A_c)=1 according to Kolmogorov’s 0-1 Law. Note that \cap_{n=1}^\infty \left[|X_n|\le \frac{a_n}{c}\right]\subset A_c and

\displaystyle \mathbb{P}\left(\bigcap\limits_{n=1}^\infty \left[|X_n|\le \frac{a_n}{c}\right]\right)=\prod_{n=1}^\infty \left(1-P\left(|X_1|>\frac{a_n}{c}\right)\right)

which is positive because \sum P\left(|X_1|>\frac{a_n}{c}\right)<\infty. Thus, \mathbb{P}(A_c)>0 and therefore, \mathbb{P}(A_c)=1. Now note that

\displaystyle \mathbb{P}\left(\lim\frac{X_n}{a_n}=0\right)= \mathbb{P}\left(\limsup\frac{|X_n|}{a_n}=0\right)=\lim_{k\to\infty} \mathbb{P}(A_{k})=1.

This completes the proof.

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