In his book "The Misbehavior of Markets", Mandelbrot introduces the Hurst exponent with a coin toss example. He says that when you toss coins for a large number of times, you can get consecutive runs of heads or tails. For instance, in a $100$ tosses game, you can get $8$ Heads one after the other and you can get $3$ Tails one after the other. The range in this example is $8 + 3 = 11$.
Now, Mandelbrot says that in a $10,000$ tosses game, which has $100$ times more tosses than the $100$ tosses game, the range is expected to be $110$, because the range grows as the square root of the growth in the number of tosses. In other words, as the number of tosses grows from $100$ to $10,000$, the range is expected to grow by ten times, from $11$ to $110$.
I tried this in R and, no. I simulated the ranges in $100, 1,000, 10,000, 100,000$, and $1,000,000$ tosses, $10,000$ simulations each. The modes of those simulations are:
$$100 \to 11; 1,000 \to 18; 10,000 \to 24; 100,000 \to 31; 1,000,000 \to 38$$
which grow in no way as the square root of the number of tosses. For instance, from a $100$ tosses to a million tosses, a growth of $10^4$, the range should grow by a factor of $100$ according to the book, but it grows by a factor of $\sim 3.5$, so the growth factor is more like a log $\quad(\log 10,000 = 4)$ than a square root ($\sqrt{10,000} = 100$).
Happy to provide the R code.
Thanks much!
Mete