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Author Topic: Monthly average USD/bitcoin price & trend  (Read 117348 times)
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dnaleor
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February 21, 2014, 10:53:11 AM
 #461

Holy shit. That blows my mind - just the numbers involved and the speed with which it can happen - and it also shows how BTC has so many unique and unpredictable aspects vs. any "traditional" tech innovation/adoption/value cycle - even compared to another disruptive game-changer.  Shocked

The first time I saw the log chart my mind was also blown. I still like watching those charts Smiley

So far, the log trend is still active. Lets hope it will continue for at least a year:
10000 USD in march 2015 Smiley


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Arriemoller
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February 21, 2014, 11:02:45 AM
 #462

I found this chart a while ago, don't remember where, but it is update daily. If you switch to the s-curve that will blow your mind even more.
https://docs.google.com/spreadsheet/ccc?key=0ArD8rjI3DD1WdFIzNDFMeEhVSzhwcEVXZDVzdVpGU2c#gid=1

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February 21, 2014, 04:12:12 PM
 #463

I found this chart a while ago, don't remember where, but it is update daily. If you switch to the s-curve that will blow your mind even more.
https://docs.google.com/spreadsheet/ccc?key=0ArD8rjI3DD1WdFIzNDFMeEhVSzhwcEVXZDVzdVpGU2c#gid=1

impressive data in terms of how you collected avg. price points daily

though as we see gox is not much suitable for the price, perhaps it should be switched to stamp(or better start weighting price from some point, like November or someting, with decreasing role of Gox) ?
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February 21, 2014, 05:50:06 PM
 #464

I found this chart a while ago, don't remember where, but it is update daily. If you switch to the s-curve that will blow your mind even more.
https://docs.google.com/spreadsheet/ccc?key=0ArD8rjI3DD1WdFIzNDFMeEhVSzhwcEVXZDVzdVpGU2c#gid=1

impressive data in terms of how you collected avg. price points daily

though as we see gox is not much suitable for the price, perhaps it should be switched to stamp(or better start weighting price from some point, like November or someting, with decreasing role of Gox) ?

Just to clarify, it's not my chart and I'm not the one updating it, I just stumbled upon it in a tread somewhere, bookmarked it, and remembered it now and thought I should share it with you.

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February 21, 2014, 06:43:46 PM
 #465

I found this chart a while ago, don't remember where, but it is update daily. If you switch to the s-curve that will blow your mind even more.
https://docs.google.com/spreadsheet/ccc?key=0ArD8rjI3DD1WdFIzNDFMeEhVSzhwcEVXZDVzdVpGU2c#gid=1

impressive data in terms of how you collected avg. price points daily

though as we see gox is not much suitable for the price, perhaps it should be switched to stamp(or better start weighting price from some point, like November or someting, with decreasing role of Gox) ?

Just to clarify, it's not my chart and I'm not the one updating it, I just stumbled upon it in a tread somewhere, bookmarked it, and remembered it now and thought I should share it with you.
The logistics model was created by "SlipperSlope", he has another thread on this as well.
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February 22, 2014, 11:51:48 AM
 #466

FWIW: This graph shows the Bitcoin price relative to the trend. It also contains quantiles of highs and lows since 2012. The price is between 38.09% and 213.45% of the trend price in 90% of all days since 2012.

More quantiles:

L:Q(0.1) = 0.4113907
L:Q(0.25) = 0.5348829

H:Q(0.75) = 1.198960
H:Q(0.9) = 1.709515

Median of the typical price T:Q(0.5) = 0.6922865

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February 22, 2014, 02:08:41 PM
 #467

FWIW: This graph shows the Bitcoin price relative to the trend. It also contains quantiles of highs and lows since 2012. The price is between 38.09% and 213.45% of the trend price in 90% of all days since 2012.

More quantiles:

L:Q(0.1) = 0.4113907
L:Q(0.25) = 0.5348829

H:Q(0.75) = 1.198960
H:Q(0.9) = 1.709515

Median of the typical price T:Q(0.5) = 0.6922865
it looks nice, but I didn't udnerstood a damn thing. can you eleborate on it a bit more? how "trend" line is calculated (is it just average of all prices? but it's percentages?)


What abs. value when L=0,3809 will be crossed?
What is these gray areas?
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February 23, 2014, 10:24:01 AM
 #468

it looks nice, but I didn't udnerstood a damn thing. can you eleborate on it a bit more? how "trend" line is calculated (is it just average of all prices? but it's percentages?)

Re: trend line, watch this: https://www.youtube.com/watch?v=LI0QYkv7--4

Given rpietilas current trend line you can calculate the trend price at x where x is the number of days since 2009-01-03.

You can calculate x from a given date, e.g. x from Feb 22 in Python:

Code:
>>> from datetime import date
>>> x = (date(2014, 2, 22) - date(2009, 1, 3)).days
>>> x
1876

Using rpietilas formula the trend price P for x = 1876 is

P = 10 ^ (0.003073 * 1876 - 2.909514) = 716.8594

On Bitstamp Feb 22 high H = 619.88. That is H / P = 87.09% of Feb 22 trend price.

What abs. value when L=0,3809 will be crossed?
What is these gray areas?

The absolute value of L = 0.3809 depends on x:

absv(L, x) = L * 10 ^ (0.003073 * x - 2.909514)

E.g. for Feb 22: 0.3809 * 10 ^ (0.003073 * 1876 - 2.909514) = 273.0518

The grey area is between highs and lows on a 3-day chart, the typical price is defined as (H + L + C) / 3. BitcoinWisdom.com 3d chart with "Settings" -> "Lines" yields a similar graph.

For me it's just an opportunity to draw funny graphs in R, don't read too much into it.
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February 24, 2014, 05:56:56 PM
 #469

it's a very interesting chart, could you please add more values (5% interval) on the y axis? thanx very interesting indeed.
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February 25, 2014, 02:01:21 PM
 #470

Hello,

I did a similar chart in r.



If the price is carrying on like this we should touch the second standard deviation soon, around 420 usd ish.

For extracting the trend I’ve used the function stl(Seasonal Decomposition of Time Series by Loess) in R

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February 25, 2014, 05:29:44 PM
 #471

Hello,

I did a similar chart in r.



If the price is carrying on like this we should touch the second standard deviation soon, around 420 usd ish.

For extracting the trend I’ve used the function stl(Seasonal Decomposition of Time Series by Loess) in R


Thank you , interesting chart. Could you please post the value of the standard deviation (sigma).
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February 26, 2014, 07:56:04 AM
 #472

Using rpietilas formula the trend price P for x = 1876 is

P = 10 ^ (0.003073 * 1876 - 2.909514) = 716.8594


Yes, I would very much like if everybody used my formula in this thread.

Otherwise casual readers cannot understand anything, nor trust anything.

The bolded figures are the parameters of the current trendline.
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February 26, 2014, 07:15:15 PM
 #473

You can calculate x from a given date, e.g. x from Feb 22 in Python:

Code:
>>> from datetime import date
>>> x = (date(2014, 2, 22) - date(2009, 1, 3)).days
>>> x
1876




The trend point can be calculated online using the wolframalpha computational search engine in two steps:

first, get the number of days since 2009-1-3:
https://www.wolframalpha.com/input/?i=number+of+days+since+2009-01-03
This URL will work for any "today"

next, using that number (today it was 1880), replace it in the following search term:
Code:

https://www.wolframalpha.com/input/?i=10+%5E+%280.003073+*+1880+-+2.909514%29


**remember to replace the 1880 number with today's correct number and run the search again.

The result is today's trendline price in USD.


Note: if someone can figure out how to encapsulate the results of the first search URL directly into the second, then this could be a single bookmark-able URL to return today's trendline value.

edit* the forum software was butchering my second URL. I had to embed it into a code tag to get it to show up properly. You will have to copy and paste it into a new browser window to use it. Again, anyone know a fix for that problem?

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February 26, 2014, 07:49:55 PM
 #474

I figured it out!

Here is a one-click URL to give you today's trendline number using WolframAlpha:
 
https://www.wolframalpha.com/input/?i=10+%5E+%28+%28+3073%2F1000000+%29+*+%28+number+of+days+since+jan+3%2C+2009%2F+days+%29+-+2.909514+%29


*edit: fixed URL
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February 26, 2014, 07:58:59 PM
 #475

I figured it out!

Here is a one-click URL to give you today's trendline number using WolframAlpha:
 
https://www.wolframalpha.com/input/?i=10+%5E+%28+%28+3073%2F1000000+%29+*+%28+number+of+days+since+jan+3%2C+2009%2F+days+%29+-+2.909514+%29


*edit: fixed URL

That is sweet! Thanks for that!

Risto, could you put this link in the OP? That would be very helpful.

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February 27, 2014, 12:35:40 PM
 #476

Hallo Risto,
What do you think about the price now, have some fiat in stamp, but have not yet decided to buy, or wait.... difficult to decide...
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February 27, 2014, 12:42:13 PM
 #477

When I look at your trendline, it seems that we are a little bit over the trendline, but who knows. Your mansion is really nice, live also in Virumaa, but it takes a lot of investment with restauration it.
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February 27, 2014, 01:39:54 PM
 #478

Hallo Risto again, as I understand you have strong connection  to Estonia, so I would like to ask you if there is Bitcoin community there? Tried to find some forums here, all these are outdated.

I don't know of it, but maybe in Tallinn.
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February 27, 2014, 02:01:59 PM
 #479

I think the charts, albeit pretty, are not so much useful to understand the future trends of bitcoin.
This chart, in my opinion, just suppose there is no changing in bitcoin vs the US$ and the price depend, heavily, just on adoption and use.

It is not so.
The inflation rate of bitcoin M0 and US$ change with time and the differential is gone from negative (against bitcoin) to positive (for bitcoin) in the years.
The differential in the inflation rate is what cause bitcoin to have a gravitational pull stronger than any other fiat currency, and is a big cause of the increase of exchange rate, adoption rate (for practical mundane reasons) and so on.

It would be pretty useful if someone could make a chart comparing the inflation rate in bitcoin with the inflation rate of USD e € and the differential.
Lower the inflation rate, at this point, faster bitcoin will suck up value from other fiats.
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February 27, 2014, 02:47:18 PM
 #480

I think the charts, albeit pretty, are not so much useful to understand the future trends of bitcoin.
This chart, in my opinion, just suppose there is no changing in bitcoin vs the US$ and the price depend, heavily, just on adoption and use.

It is not so.
The inflation rate of bitcoin M0 and US$ change with time and the differential is gone from negative (against bitcoin) to positive (for bitcoin) in the years.
The differential in the inflation rate is what cause bitcoin to have a gravitational pull stronger than any other fiat currency, and is a big cause of the increase of exchange rate, adoption rate (for practical mundane reasons) and so on.

It would be pretty useful if someone could make a chart comparing the inflation rate in bitcoin with the inflation rate of USD e € and the differential.
Lower the inflation rate, at this point, faster bitcoin will suck up value from other fiats.

I agree with this underlying point. Trend charts are nice, and can often tell a story, but can often be largely useless in terms of prediction.

On net, Bitcoin's "price" is an exchange rate. Therefore, I also agree that the $US changing money supply will impact Bitcoin price changes in US$. Think about it this way, if there are more dollars floating around (or being printed), the value of a static good should increase (via inflation). The same holds true for Bitcoin, perhaps even more so, since some are using it as a hedge against inflation. In other words, demand will increase when the Fed declares QE-to-infinity part II. This was true towards the end of of 2013 when Bitcoin hit new highs while Bernanke reneged on promises to start cutting monthly QE.... the price for Bitcoin jumped in response. Now, in 2014, since Yellen took over they have begun monthly cutting to QE (despite a recent "pause), Bitcoin price is relatively lower. Don't get me wrong, other elements (Mt. Gox, etc) certainly play a huge role in fluctuations, but some of these elements are unpredictable. At the very least, domestic currency elements should be included in a Bitcoin price model.

If someone posts the monthly Bitcoin data history here (up-to-date). I would be happy to create a quick model, incorporating M1 or M2.
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