Topic: Logarithmic (non-linear) regression - Bitcoin estimated value - page 14. (Read 117739 times)

nice charts

will folow your posts from now on

edit: left you a small tip

Nice post & analysis, Trolololo. Following.

I made a similar observation earlier this month in Stephen Reed's thread, about what looked like an increasing time span between reaching the next order of magnitude in network size, but didn't follow up on it (shameless plug to my own post :D).


A question.

I'm not sure about the exact type of growth of your function. What you seem to be mapping is logarithmic growth (slow) on a log chart (fast). Stripped of its minor constants, your formula is of the form 10^ln(t) for time = t. ln(t) grows extremely slow over time, but the result is used as a positive, growing exponent.

It seems to fall somewhere between linear growth and exponential growth, and it isn't bounded either (like in Stephen's model). I was wondering if someone with more knowledge on functional growth could answer this once and for all for me, have been wondering about this for a while now. (EDIT: I'm wondering if it could be an instance of so called sub-exponential growth)


A critical remark.

While I personally, intuitively, find a price function with a declining growth rate (like yours) more plausible than the constant growth rate models that have been presented on this forum (i.e. the "loglinear models" you linked to as well), one problem still remains:

Price tends to "jerk around" all those models.

I remember that, late last year, when price exceeded even the loglinear model's predictions, some analysis was posted that suggested a superexponential price function to model BTC price.

Then came the first leg of the 2013/2014 correction, and suddenly the loglinear models were all the rage again.

Now, the correction continues, and you suggest (with good reasons, I agree) a model based on an below exponential growth assumption. But I'm afraid all it takes is another year of bear market (or perhaps, a sudden rally of huge proportions), and we need to re-adjust our assumption for what the "best" growth type for our model is...

Here's what I'm trying to say: I am using technical (i.e. historic price based) methods myself all the time for predicting price on the short term. However, I start to think that, on a long enough time scale, fundamentals govern the price function. So a model like yours (or Stephen's, or rpietila's), that are essentially an extrapolation from an (admittedly well fitted) function on the historic price data might come to its limits.

I am thinking that perhaps the only semi-reliable way to go about mapping the "long term trend" is Peter R.'s way: finding a proxy for network size, and then modeling expected price/mcap as a function of network size.

See for example here: https://bitcointalksearch.org/topic/m.9059346

He still makes a number of assumptions (Metcalfe's law, for example), and in a way, his method only shifts the problem (because now we are trying to predict, i.e. extrapolate, network size), but at least his predicted numbers will rarely be so out of tune with reality as the pure time series models can be at times.

With only 1550 days of prices, it's quite weird to estimate the value for day #24.098 (01-01-2075).

But let's suppose that the price stays flat at 370 for 5 more years (from today to 01-01-2020).
That would mean we have around 5500 days of prices.
The logarithmic regression would throw a estimated value of 961 k$ by 01-01-2075.

That's a more realistic value than any linear regression model.

Thanks for the date.

Excel is not perfect. Did you reach the line limit ? (1 048 576 lines)

Thank you!

1.000.000 on 06-09-2026

I would like extend the chart to that date, but by excel worksheet doesn't want to. I don' know why.

Wow, nice work!
Thread watched and notified.
Just gave a small tip.

Your work is really great. This trendline seems realistic.

Could you provide a date for the one million dollar price ? Or extend your chart a little bit ?

Added to the OP:
Calculate today's trendline price HERE

Interesting chart. It's also in line with the hyperinflationary QE-to-infinity scenario which is to unfold when stock and other markets crash. Of course, that $10k in 2017 won't buy you as much as it can buy today.

tomorrow came... please tell when million dollar btc

I will answer you tomorrow.

Edit: 06-09-2026

To figure out what can happen in the future price and volatility, read these interesting thoughts: 100,000 block countdown - What will happen at the next halving?

By year 2075 I will be dead.

The curve will always grow, but slowlier and slowlier as time goes by. Just like the Bitcoin emission curve.
This logarithmic regression is way better than the linear regression. But it's just a model, not a crystal ball.

The curve will flatten or steepen depending on the future price fluctuations, but not much.
I will recalculate the regression from time to time. Maybe monthly, or once every three or four months.

I made the chart for myself, and I later thought that it would be worth sharing it with you all.

What price do you get in 2075? In my opinion the "equilibrium" price of Bitcoin is one of the easier numbers to make rational arguments about (thermodynamics is always on sounder footing than kinetics, etc.).
For example, if you get $1 trillion per BTC in 2075, I would say the model is problematic, however well fitted. If you get something in the $1-10 million range, then you're probably in the ballpark. (these models assume a certain optimism about adoption already)

Probably about right. 

But let's not forget the massive volatility we will have getting there!

-37% (it's the calculation of 1 - 10^-0.2)

Thanks. I'll fix that.


Edit: fixed

-25% or -37% on the y-axis of the 1Bgn graph? The right and left axes disagree.

In what year does your regression intersect with $1M USD?