# Proof the increment variance of the Scaled Random Walk

Start by defining the Symmetric Random Walk:

$$M_t = \sum_{i=1}^{t}X_i, ~~ \text{with}~X_0=0$$

where $X_i$ is equal to 1 or -1 with $p=(1-p)=0.5$.

Consider $t > s$, the variance of its increments is:

\begin{equation} \begin{split} VAR(M_t - M_s) & = VAR \Big( \sum_{i=s+1}^tX_i\Big)~\text{by indepence of} ~ X_i \\ & = \sum_{i=s+1}^t VAR(X_i) = t-s \end{split} \end{equation}

Now define the Scaled Symmetric Random Walk:

$$W^{(n)}(t) = \begin{cases} \dfrac{1}{\sqrt{n}}M_{nt}, & \mbox{if }~t=\dfrac{m}{n}~\in~ \mathbb{N} \\ \mbox{linear interpolation}, & \mbox{if } t~\in~ \Big( \dfrac{m}{n}, \dfrac{m+1}{n} \Big) \end{cases}$$

Now suppose $~t > s~$ and $~t = l/n~$ and $~s = m/n~$ are integers, now how is possible to obtain the following variance?

$$VAR(W^{n}(t) - W^{n}(s))$$

I tried this way:

\begin{equation} \begin{split} VAR(W^{n}(t) - W^{n}(s)) & = VAR\Big( \dfrac{1}{\sqrt{n}} (M_l - M_m) \Big) \\ & = \dfrac{1}{n}VAR(M_l - M_m) \end{split} \end{equation}

Then by applying the passages of the normal random walk reported above, I obtain:

$$VAR(W^{n}(t) - W^{n}(s)) = \dfrac{1}{n} (t-s)$$

But I know that the correct formula should be $t-s$. Where is my error?

You forget an $n$ in the index. After "I tried this way", second equivalence, you should apply:
$$M_l - M_m = M_{tn} - M_{sn}$$
• No because it is $M_{tn}$ that becomes $M_{l}$ since $t = l/n$. – Archimede Aug 30 '17 at 14:14