In finance we have what is called a Martingale approach.
Basically we say that all the information for potential future prices is contained in the current existing price and also (and this is the Martingale part) that the conditional expectation for later prices only depends on the current price.
You also have option pricing which takes a very similar approach but the volatility is captured in what is called a Brownian Motion or Wiener process.
If you have volatility information, then what you can do is simulate the process so many thousands of times and then get the average path for the amount of time simulated and this can be used to see the behavior of the process under the Wiener/Brownian motion process assumptions.
For this you will need to simulate from a Normal distribution and in Excel this is given by the function NORMDIST:
An Introduction to Excel's Normal Distribution Functions
So what you would do is calculate say 5000 simulations for each tick and then get the average and standard deviation of each tick and plot that if you wanted to.
Also this model is a simple one and if you have other assumptions or extra information, then it may not be adequate at all.
What kind of tick size were you thinking of?