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Consider the random walk $S_n = \sum_{i=1}^n (X_i-1)$ where $X_i$ are i.i.d. with exponential distribution and mean $1$, i.e. $P(X_i \leq x) = 1-e^{-x}$. I am trying to figure out the probability $p_n$, that the random walk has never reached a negative value after $n$ steps. I have obtained the exact values for the first small $n$:

$p_1 = e^{-1}$

$p_2 = 2e^{-2}$

$p_3 = \frac{9}{2}e^{-3}$

$p_4 = \frac{64}{6}e^{-4}$

I have noticed the pattern, that apparently $p_n = \frac{n^{n-1}}{(n-1)!}e^{-n}$. I have also done some numeric simulations that seem to confirm that this is in fact the answer. However, I have been unable to prove this. I have tried using the law of total probability, but there I then need to determine the probability that a random walk like above never reaches a negative value if it starts at a specific (positive) value, which I don't know how to compute.

If the exact value is too difficult to prove, I would also be content with an upper bound that also converges to 0 for large $n$. Any insight is greatly appreciated.

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This is not a full answer. I found a different perspective to view the problem in, which turns the question from a complicated integral to a complicated discrete summation.


Consider a Poisson process, with unit density, on the positive real line. This means that for any $0<a<b$, the number of arrivals in $[a,b]$ has the distribution $\text{Poisson}(b-a)$. If you number the arrivals $0<A_1<A_2<\dots$, with the convention $A_0=0$, then it is well known that the inter-arrival times $A_k-A_{k-1}$ all have an exponential distribution with rate $1$. So, from now on, I will identify $$X_k=A_{k}-A_{k-1}.$$

Now, how do your events related to the Poisson process?

  • You are requiring $(X_1-1)\ge 0$, which implies that $A_1=X_1\ge 1$. That is, the first arrival happens after time $1$, so there are no arrivals in the interval $(0,1)$.

  • Next, you require $(X_1-1)+(X_2-1)\ge 0$, which implies $A_2=X_1+X_2\ge 2$. That is, the second arrival happens after time $2$, there is at most one arrival in the interval $(0,2)$.

Continuing in this fashion, for each $k\in \{1,\dots,n\}$, the event $(X_1-1)+\dots+(X_k-1)\ge 0$ is equivalent to the Poisson process having at most $k-1$ arrivals in the interval $(0,k)$. To simplify this further, for each $k\in \{1,\dots,n\}$, define $Z_k$ to be the number of arrivals in $(k-1,k)$. Then, let $$ E_k=\{Z_1+Z_2+\dots+Z_k\le k-1\}. $$ We have shown that $$ p_n=\mathbb P(E_1\cap E_2\cap \dots \cap E_n). $$ Let us see how this plays out when $n=3$. According to above, $$ P_3=\mathbb P(Z_1\le 0\;\cap\; Z_1+Z_2\le 1\;\cap\;Z_1+Z_2+Z_3\le 2) $$ For these three inequalities to be satisfied, the vector $(Z_1,Z_2,Z_3)$ must be one of five possibilities: $(0,0,0),(0,0,1),(0,0,2),(0,1,0),$ or $(0,1,1)$. We can easily find the probability of each of these vectors, since $Z_1,Z_2,Z_3$ are independent, and each has a $\text{Poisson}(1)$ distribution. The result is $$ {e^{-3}}\left(\frac1{0!\cdot0!\cdot0!}+\frac1{0!\cdot0!\cdot1!}+\frac{1}{0!\cdot0!\cdot2!}+\frac{1}{0!\cdot1!\cdot0!}+\frac{1}{0!\cdot1!\cdot1!}\right)=\frac92e^{-3} $$ For general $n$, you need to enumerate all sequences $(z_1,\dots,z_n)$ with the property that the $z_1+\dots+z_k\le k-1$ for each $k\in \{1,\dots,n\}$, and then compute the sum of $$ e^{-n}\frac1{z_1!\cdot z_2!\cdots z_n!}\tag1 $$ over all such valid sequences.

I find it intriguing that for each $n$, the number of valid sequences is always equal to the $n^\text{th}$ Catalan number! Specifically, we can give a bijection between valid sequences $(z_1,\dots,z_n)$, and lattice paths from $(0,0)$ to $(n,n)$ which never go above the line $y=x$. I give more details in the answer to this question.

To see the combinatorial nature of this problem, note that proving the sum $(1)$ over all valid sequences is equal to $e^{-n}n^{n-1}/(n-1)!$, is equivalent to proving $$ {n^n}=\sum_{\substack{{z_1,\dots,z_n\ge0}\\ {z_1+\dots+z_k\le k-1\;\forall k}}}\frac{n!}{z_1!\cdots z_n!} \tag2$$ Note that the left hand side enumerates a nice combinatorial object, namely the set of functions from an $n$-element set to itself. Furthermore, the right hand side is a sum of integers, and it also has a nice combinatorial interpretation. Therefore, I suspect that you can give a bijective proof of $(2)$. However, I cannot imagine what the bijection is.

Mike Earnest
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