How about this method:
1)Get the gox historical daily prices
2)Calculate the day-to-day percent changes, ie (Price[n+1] - Price[n])/Price[n]
3)Create a markov chain starting at the most recent price
4)Sample a price change from the distribution of differences in the historical data (see topright panel below)
5)Update Price by one day in future
6)Goto 4
Example outputs:
Overall Posterior Distributions:
Interpretation:
30 days from today there 95% probability the price will be between 62.5 and 320.7 usd, 67% probability it is between 105.7 and 219.6 USD, and the expected value is either 181 or 169 usd depending on whether you prefer the mean or median as your estimator.