Apologies I was intending to make following correction and then we had a brown out and I fell asleep.
It is roughly saying we won't significantly surpass $1000 in 2014. I don't know where the correctly fitted curve would be right now, so I can't project where the price should be now and where it will be nominally. I think the slope projection is more close to accurate, so we can say that if the theory is correct (that distribution of money holders is a power law distribution as the cited research and common knowledge says it always is), then price appreciation will slow down specifically to 0.05 units on the log 10 chart per month where 1 unit is 10X appreciation. So if we bottom at $400, then price after 20 months should be $4000. Again this is a very rough eyeballed fit and would expect the refined fit to have a slightly higher slope maybe 0.06, so make that 16 months instead.
The red line below is a power law distribution for B=0.5 which you can see above is the value of B I fitted.
What that distribution says is that the rich hold most of the percentage of wealth, which we know is in fact always true. And the fitting of the cumulative distribution function to BTC price is the theoretical claim that earlier adopters will be more wealthy (by now) than later ones.
The research I cited points out is that the masses use money as a unit-of-exchange, not as a store-of-value.
However does the Metcalf's law value of money (which Peter R has shown BTC mcap and thus price is tracking) where the value is proportional to the square of the number of nodes in the network nullify my use of a power law distribution? I.e. do the wealthy not create (proportional to their wealth) more network nodes (e.g. unique active BTC addresses) than the masses?
I see the really diehard power users (e.g. SlipperySlope and Peter R) are both talking about creating a new node every day. Thus this anecdotally supports that the power law distribution applies correctly here.
Thus I think we need to take this theory seriously. It might be the correct growth curve. The linear one with a least squares fit seems really out-of-touch with historical data. It totally ignores the shape of the earliest adoption curve up to July 2011. Risto's explanation was the early adopters were bad speculators and bid the price up too much, but my interpretation is they are the most wealthy now and they were the most powerful because they are early adopters. The least squares fitting of a line to a curved adoption could possibly be (confirmation bias in play as) an (emotional "to the moon") attempt to force a linear projection on a growth curve which obviously was not always linear. Has it become linear since January 2012?
I very much doubt it!
Convince me? Risto how do you analytically defend your linear least squares fit that makes you so sure of everything and gives you the audacity to browbeat all the bears?
Add: why don't stocks follow this log-logistic curve? Maybe they do (?), if we don't compress the early adopters into a single event IPO. Also can a stock issue have network effects, i.e. does Metcalf's law apply to company shares? Seems to me yes if the shareholders network amongst themselves, but much less so than a network of money holders.
Add: Fact is the slope during the runup to July 2011 was 0.33 per month. Since Jan 2012, it has been 1/4 of that 0.08 roughly. Why should we expect the slope to not decline again? Why should the pace of adoption remain constant? Seems intuitively unlikely to me. Pace of adoption should slow as we slog into the less astute demographics. Larger mass with more inertia grows more slowly than smaller mass with nimble inertia.
The red line below is a power law distribution for B=0.5 which you can see above is the value of B I fitted.
What that distribution says is that the rich hold most of the percentage of wealth, which we know is in fact always true. And the fitting of the cumulative distribution function to BTC price is the theoretical claim that earlier adopters will be more wealthy (by now) than later ones.
The research I cited points out is that the masses use money as a unit-of-exchange, not as a store-of-value.
However does the Metcalf's law value of money (which Peter R has shown BTC mcap and thus price is tracking) where the value is proportional to the square of the number of nodes in the network nullify my use of a power law distribution? I.e. do the wealthy not create (proportional to their wealth) more network nodes (e.g. unique active BTC addresses) than the masses?
I see the really diehard power users (e.g. SlipperySlope and Peter R) are both talking about creating a new node every day. Thus this anecdotally supports that the power law distribution applies correctly here.
Thus I think we need to take this theory seriously. It might be the correct growth curve. The linear one with a least squares fit seems really out-of-touch with historical data. It totally ignores the shape of the earliest adoption curve up to July 2011. Risto's explanation was the early adopters were bad speculators and bid the price up too much, but my interpretation is they are the most wealthy now and they were the most powerful because they are early adopters. The least squares fitting of a line to a curved adoption could possibly be (confirmation bias in play as) an (emotional "to the moon") attempt to force a linear projection on a growth curve which obviously was not always linear. Has it become linear since January 2012?
I very much doubt it!
Convince me? Risto how do you analytically defend your linear least squares fit that makes you so sure of everything and gives you the audacity to browbeat all the bears?
Add: why don't stocks follow this log-logistic curve? Maybe they do (?), if we don't compress the early adopters into a single event IPO. Also can a stock issue have network effects, i.e. does Metcalf's law apply to company shares? Seems to me yes if the shareholders network amongst themselves, but much less so than a network of money holders.
Add: Fact is the slope during the runup to July 2011 was 0.33 per month. Since Jan 2012, it has been 1/4 of that 0.08 roughly. Why should we expect the slope to not decline again? Why should the pace of adoption remain constant? Seems intuitively unlikely to me. Pace of adoption should slow as we slog into the less astute demographics. Larger mass with more inertia grows more slowly than smaller mass with nimble inertia.