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

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

I've managed to use the Borel-Cantelli lemma to show that P(|X_n| \geq n \text{ infinitely often}) = 1, 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.
 
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