So bottom line: what's the resulting price projection?
Something like this. We've seen 900% growth this year as opposed to 3,800% in the 2011 spike.
Topic: Current Situation vs. 2011 Bubble - you ain't seen nothin' yet! (Read 3280 times)
Something like this. We've seen 900% growth this year as opposed to 3,800% in the 2011 spike.
update 2013-04-03 (static image @ 145usd/btc)
we are in rough see now...
we are in rough see now...
So bottom line: what's the resulting price projection?
By the looks of it - if we were in a bubble it would be about 600.
People are much more afraid of a bubble now than back then, though.
I guess that depends what price they paid for the BTC.
So bottom line: what's the resulting price projection?
By the looks of it - if we were in a bubble it would be about 600.
People are much more afraid of a bubble now than back then, though.
I guess that depends what price they paid for the BTC.
So bottom line: what's the resulting price projection?
By the looks of it - if we were in a bubble it would be about 600.
People are much more afraid of a bubble now than back then, though.
By the looks of it - if we were in a bubble it would be about 600.
I have to admit, made me laugh
Of course this time everything will be EXACTLY the same as before, only scaled up. 
hehe.
It applies a very simple to implement/calculate long time filter to the price. Filtered data is the orange dotted line in the upper chart. Similar to a "simple moving average", SMA or probably more similar to an "exponential moving average". Data resolution is 17-19 mins so you can calculate the time constant of the filter if you like.
Then it takes the difference between the price and the filtered curve and sets it in relation to the filtered curve.
The idea is to remove the trend and only show short term movement in a normalized way so the situation now can be properly compared to earlier peaks.
It applies a very simple to implement/calculate long time filter to the price. Filtered data is the orange dotted line in the upper chart. Similar to a "simple moving average", SMA or probably more similar to an "exponential moving average". Data resolution is 17-19 mins so you can calculate the time constant of the filter if you like.
Then it takes the difference between the price and the filtered curve and sets it in relation to the filtered curve.
The idea is to remove the trend and only show short term movement in a normalized way so the situation now can be properly compared to earlier peaks.
very interesting! what is the period for the moving average? It's based on minute data?
with info here: http://en.wikipedia.org/wiki/Moving_average#Exponential_moving_average
...you can calculate that the filter is similar to an exponential moving average of a factor of 1224 (note that this is quite different from SMA).
Quote
has anyone seen similar metrics used to analyze price data in other markets?
This would interest me, too. Just pulled it out of my... I guess normal stock prices do not fluctuate by such large factors. But with Bitcoin an approach like this seems necessary.
By the looks of it - if we were in a bubble it would be about 600.
I have to admit, made me laugh
So bottom line: what's the resulting price projection?
By the looks of it - if we were in a bubble it would be about 600.
So bottom line: what's the resulting price projection?
So the diagram states that the price today is not as far off from it's long term average as it was back then? We only saw a 500% increase instead of 3500% given the same time constants?
Yes, its a little hard to understand but compare the top diagram blue line from April-July 2011 and compare that to Jan 2013 onwards. April-July 2011 shows a much steeper rise.
So the diagram states that the price today is not as far off from it's long term average as it was back then? We only saw a 500% increase instead of 3500% given the same time constants?
Can you explain the second chart in a little more detail?
sure:Code:
# simple iir filter
integrator = self.chartData[0,1]
for i, d in enumerate(self.chartData):
integrator += (float(d[1]) - integrator) / 50000.0
self.filtY[i] = integrator
# "momentum"
for i in range(len(self.chartData)):
Y = self.filtY[i]
self.indicatorY[i] -= Y
self.indicatorY[i] /= Y
self.indicatorY[i] *= 100.0
Yes, yes. But what does it mean?
first part does an "average" between a lot of numbers, like drawing a very smooth line through the data points.
the second part is a bit odd to me, because i don't know with what value "indicatorY" begins. maybe, it subtracts this smoothed value from the chart data and calculates the percentage change (divide + multiplication by 100)
hehe.
It applies a very simple to implement/calculate long time filter to the price. Filtered data is the orange dotted line in the upper chart. Similar to a "simple moving average", SMA or probably more similar to an "exponential moving average". Data resolution is 17-19 mins so you can calculate the time constant of the filter if you like.
Then it takes the difference between the price and the filtered curve and sets it in relation to the filtered curve.
The idea is to remove the trend and only show short term movement in a normalized way so the situation now can be properly compared to earlier peaks.
It applies a very simple to implement/calculate long time filter to the price. Filtered data is the orange dotted line in the upper chart. Similar to a "simple moving average", SMA or probably more similar to an "exponential moving average". Data resolution is 17-19 mins so you can calculate the time constant of the filter if you like.
Then it takes the difference between the price and the filtered curve and sets it in relation to the filtered curve.
The idea is to remove the trend and only show short term movement in a normalized way so the situation now can be properly compared to earlier peaks.
new chart 2013-03-20
So if I read this right you're saying we haven't even started yet.
Can you explain the second chart in a little more detail?
sure:Code:
# simple iir filter
integrator = self.chartData[0,1]
for i, d in enumerate(self.chartData):
integrator += (float(d[1]) - integrator) / 50000.0
self.filtY[i] = integrator
# "momentum"
for i in range(len(self.chartData)):
Y = self.filtY[i]
self.indicatorY[i] -= Y
self.indicatorY[i] /= Y
self.indicatorY[i] *= 100.0
Yes, yes. But what does it mean?
Can you explain the second chart in a little more detail?
sure:Code:
# simple iir filter
integrator = self.chartData[0,1]
for i, d in enumerate(self.chartData):
integrator += (float(d[1]) - integrator) / 50000.0
self.filtY[i] = integrator
# "momentum"
for i in range(len(self.chartData)):
Y = self.filtY[i]
self.indicatorY[i] -= Y
self.indicatorY[i] /= Y
self.indicatorY[i] *= 100.0
new chart 2013-03-20
haha bubble talkers are funny they wanna decrease but valu enever decrease for bitcoin hold = rich easy concept easy for all people to make money
bitcoin up 1000% 1 year this year 5000% we reach price 1000 $ to the moon!!!!
hold = rich easy concept easy for all people to make moneybitcoin up 1000% 1 year this year 5000% we reach price 1000 $ to the moon!!!!
there is still allot of room just to beat a recent bubble
the question is Zimbabwe did produce anything except money ?
I love this chart! the question is Zimbabwe did produce anything except money ?
there is still allot of room just to beat a recent bubble
the question is Zimbabwe did produce anything except money ?
the question is Zimbabwe did produce anything except money ?
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