Now let's start the
Accountable Prediction(TM) competition. (I may move this to another thread if it catches on).
The first task is to predict, what is the price in 2014-5-17 (daily average Bitstamp).
Give your answer as a probability distribution where each USD value between 0-100,000 is assigned a % probability and these values add to 100%. All answers given in 24 hours from the timestamp of this post take part in the competition.
And example and my official prediction is the following:
I am willing to predict where the price is 2014-5-17 (30 days from now) volume weighted average Bitstamp price:
Price in USD range; probability
4466-100000; 0.1%
2818-4465; 0.4%
1778-2817; 2.0%
1413-1777; 2.0%
1122-1412; 3.0%
1000-1121; 2.5%
891-999; 3.5%
794-890; 5.5%
708-793; 8.0%
631-707; 14.0%
562-630; 18.0%
501-561; 17.0%
447-500; 9.0%
398-446; 6.0%
355-397; 4.0%
316-354; 2.0%
251-315; 2.0%
0-250; 1.0%
Let's suppose that price ends up being
$600. I assigned 18.0% to this band which consists of 69 dollars. Therefore my probability density is 18.0% / 69$ =
0.2609 %/$.
If the price were
$400 instead, 6.0% / 49$ =
0.1224 %/$.
An outlier like a doubling the price to
$1,000 would have a quite small probability density: 2.5% / 122$ =
0.0205 %/$.
Once the price is determined (daily volume weighted average rounded to the nearest full dollar) and the probability density of each prediction at that price is calculated, a
geometric mean of the predictions is calculated. In this example, if the figures above were the contestants' probability densities at the "winning number", their geometric mean is: (0.2609*0.1224*0.0205)^(1/3) % = 0.0868 %.
Then we award plus points to the ones who did better than the mean, and minus points to the ones who did worse:
0.2609 / 0.0868 - 1 = 2.004
0.1224 / 0.0868 - 1 = 0.410
1 - 0.0868 / 0.0205 = -3.237
The point system compares the relative accuracy of different people's forecasts, and the average of the points over several prediction rounds gives a better idea whether this person has the hunch over future prices or not. To predict effectively you should know the system which penalizes severely if you have grossly underestimated the probability of something, yet it happens. It ruins your whole score. Also you should know the distribution of historical results, which for 30 days period is
listed here.