TITLE: How to show $M_n = X_n^2-n$ is a martingale?
QUESTION [6 upvotes]: Let $X_n, n = 0, 1, 2, . . .$ denote an unbiased Normal Random Walk.
$X_0 = 10$, and $X_{n+1} = X_n + Y_{n+1}$, with $\{Y_n\}$ are i.i.d. $N(0, 1)$.
Then how can I show that:
A) $M_n = X_n^2-n$ is a martingale
Find the value of:
B) $\mathbb{E}M_{20}$
Does the answer lie in reformulation $X_n = X_{n+1} - Y_{n+1}$ ?
And then:
$$X_n = X_{n+1} - Y_{n+1} \implies X_n^2 = (X_{n+1})^2 - 2X_{n+1}Y_{n+1} + (Y_{n+1})^2$$
And then we proceed with
$$\mathbb{E}[(X_{n+1})^2 - 2X_{n+1}Y_{n+1} + (Y_{n+1})^2 -n| \mathcal{F}_s], s \leq n+1$$
$$\mathbb{E}[(X_{n+1})^2 | \mathcal{F}_s] - 2\mathbb{E}[X_{n+1}Y_{n+1}|\mathcal{F}_s] + \mathbb{E}[(Y_{n+1})^2|\mathcal{F}_s] - \mathbb{E}[n | \mathcal{F}_s]$$
Is this right so far? if not, where I have I made a mistake, and how should I proceed?

REPLY [2 votes]: Let's look at $\mathbb{E}[X_{n+1}^2-(n+1)|F_n]$ (take $s=n$). We need show it equals to $X_n^2-n$. Since $X_{n+1}=X_n+ Y_{n+1}$ It should be 
$$
\mathbb{E}[X_{n}^2|F_n]+2\mathbb{E}[X_{n}Y_{n+1}|F_n]+\mathbb{E}[Y_{n+1}^2|F_n]-\mathbb{E}[n+1|F_n]
$$,
Since $X_{n}$ is measurable w.r.t. $F_n$, and $Y_{n+1}$ is independent of $F_n$ (for which we can "take out what is known, and by the assumption $Y_n$ is $\mathcal{N}(0,1)$ distributed, we get above equals
$$
X_{n}^2+2X_{n}\mathbb{E}[Y_{n+1}|F_n]+\mathbb{E}[Y_{n+1}^2]-(n+1),
$$
$$
=X_{n}^2+2X_{n}\mathbb{E}[Y_{n+1}]+\mathbb{E}[Y_{n+1}^2]-(n+1).
$$
Since $\mathbb{E}[Y_{n+1}]=0$, it's easy to see $\mathbb{E}[Y_{n+1}^2]=1$. Hence we reach
$$
=X_{n}^2-n.
$$