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.

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

https://i.imgur.com/U5xw3Ea.png

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:


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.


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.

Hello,

I did a similar chart in r.

https://i.imgur.com/0qdXSfK.png

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

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.

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

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...

I don't know of it, but maybe in Tallinn.

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.

Cash and castles