Prove: Let $X_1 ,X_2 , ... , X_n , ...$ be i.i.d. random variables with $\mathbb{E}[X_1^+]=\mathbb{E}[X_1^-]=+\infty$.
If $S_n=\sum_{i=1}^{n}{X_i}$, then $$\limsup_{n\rightarrow\infty}{\frac{S_n}{n}=+\infty}\text{ a.s., }\liminf_{n\rightarrow\infty}{\frac{S_n}{n}=-\infty}\text{ a.s.}$$
I have proven that $$\mathbb{P}\left(\left\{\omega :\limsup_{n\rightarrow\infty}{\left|\frac{S_n}{n}(\omega)\right|=+\infty}\right\}\right)=1,$$
so at least one of $$\mathbb{P}\left(\left\{\omega:\limsup_{n\rightarrow\infty}{\frac{S_n}{n}(\omega)=+\infty}\right\}\right)=1\text{ and }\mathbb{P}\left(\left\{\omega:\liminf_{n\rightarrow\infty}{\frac{S_n}{n}(\omega)=-\infty}\right\}\right)=1$$ is true, but I don't know how to prove both of them.
Update: According to the paper The strong law of large numbers when the mean is undefined (Erickson K B, 1973), this proposition is wrong.