Can \limsup and \liminf of IID RVs Be Shown to Be Unbounded?

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[tex]X_1, X_2, \ldots[/tex] are iid random variables with [tex]P ( X_1 = n ) = P ( X_1 = - n ) = \frac{ c }{ n^2 \log n }[/tex] where c makes the probabilities sum to one. Define [tex]S_n = X_1 + \ldots + X_n[/tex]. We want to show that
[tex]\limsup \frac{S_n}{n} =\infty[/tex] and [tex]\liminf \frac{S_n}{n} = -\infty[/tex] almost surely.

I've managed to use the Borel-Cantelli lemma to show that [tex]P(|X_n| \geq n \text{ infinitely often}) = 1[/tex], but I can't pass to the lim sup/inf. Any help/suggestions would be appreciated.
 
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Suppose limsup S(n)/n is not infinity; instead limsup S(n)/n = m where m is finite...
 
Note that if S(n)/n were bounded then X(n)/n = S(n) - (1-1/n)S(n-1) would also be bounded. Can you show that this is false?
Once that's done, Kolmogorov's 0-1 law should finish it off.