Re: Wall Observer BTC/USD - Bitcoin price movement tracking & discussion
"2x per year" trend seems invalidated. Oh well. It's still growing.
Can't you just shift it to some other convenient exponential variant? How about 1.8x hahahaha.. and then later 1.5x.. but then many of us likely appreciate that many new adoption curves (to the extent that prices are reflected therein) would likely have some kind of a curve rather than straight line, no?
As I see it one of the main problems with all the "models" *and* interpretation/expectation of models is they tend to be biased to various schelling points and oversimplification of formulas:
2x per year (has never actually happened exactly, right?)
The market cap of gold (why?),
Stock to flow (as if the only thing that matters is supply)
Some proprietary log curve or two (yeah... because it's a little complicated this simple formula will be righter!)
And my fav so far: 100k by the end of December! (TWO schelling points in one!)
Supercycle! (just picking on myself... based on greed, and sort of an anti-model really.)
Oh, and there is one more (for THIS list)... but this one is part of the holy choirbook, so people might not like to call it a broken model "The four year cycle". This one is at least supported by some fairly strong design forces. But it still only takes into account a limited number of extremely important things. Ignoring completely things like the price of electricity, the proliferation of mining, the reaction of governments, and so on. And I have to also point out that it has nothing to do with "four years" but we humans like to call it something we can easily relate to.
And ALL OF THIS exists in the extremely long shadow of the world macroeconomic condition and the strength of the worlds unit of account, the US DOLLAR.
Whatever your model... it will be instantly distorted by what happens with the mighty $$$. And the price of important commodities like food and power in THAT asset.
And while we are on THAT topic... Food and Power. We are currently watching an effort unfold by supragovernmental forces to take control of the food supply and energy creation in The Ukraine, The Netherlands, The Canada (I don't see why .ca can't have an article too!), The New Zealand, and so on.
In my opinion... gone are the simple days when we could predict shit, really.
But Bitcoin is still the best thing going for value storage, and most likely growth depending on your time horizon.Have a nice Friday WO!
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Friday morning goobly gook...test on Monday
listed in order of personal preference
'A SOMA forcast is straight out of ones ass'
https://bitcointalk.org/index.php?topic=178336.0
'A naive forecast is one in which the forecast for a given period is simply equal to the value observed in the previous period.'
https://www.statology.org/naive-forecast-excel/
'Time series datasets are the most widely generated and used kind of data in any business. They are used both in understanding the past and predicting the future.'
https://towardsdatascience.com/time-series-forecasting-from-naive-to-arima-and-beyond-ef133c485f94
'Triple Exponential Smoothing method models the next time step as an exponentially weighted linear function of observations at prior time steps, taking trends and seasonality into account.'
https://machinelearningmastery.com/time-series-forecasting-methods-in-python-cheat-sheet/
Code:
# HWES example
from statsmodels.tsa.holtwinters import ExponentialSmoothing
from random import random
# contrived dataset
data = [x + random() for x in range(1, 100)]
# fit model
model = ExponentialSmoothing(data)
model_fit = model.fit()
# make prediction
yhat = model_fit.predict(len(data), len(data))
print(yhat)
from statsmodels.tsa.holtwinters import ExponentialSmoothing
from random import random
# contrived dataset
data = [x + random() for x in range(1, 100)]
# fit model
model = ExponentialSmoothing(data)
model_fit = model.fit()
# make prediction
yhat = model_fit.predict(len(data), len(data))
print(yhat)
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gm guy says gm