Unimpressive. A model is cannot be made simply by fitting a curve.
The main problem with your "model" is that it changes over time. If you fit the curve in the past, you got different parameters. If you fit the curve next year, you will get different parameters. It's a useless "model".
1) We do that all the time in Physics. Here, for example, listen to this talk:
I'm going to try no matter what to explain and spread the message, but have you ever heard of Kepler's Laws? How do you think he found them? By exactly fitting the log of the distance of the planets vs the logs of the time it takes the planet to go around the sun. This is how he discovered one of the most important laws in astronomy. Kepler's model of the solar system is still used today.
Tell me again how fitting doesn't allow us to make a model?
Fitting allows you to make a model, but a curve fitting is not a model. Kepler's Laws describe the characteristics of the orbits of the planets, but they are not the model itself.
Here's another astronomical example. Hubble observed that the red shifts of galaxies are roughly proportional to to their distance. Here is the graph:
https://en.wikipedia.org/wiki/Hubble%27s_law#/media/File:Hubble_constant.JPGNote that neither the graph nor Hubble's constant are the model. They are observations that support the model of the the expansion of the universe.
Likewise, your curve mimics Bitcoin's price over time, but it does little to explain its nature. It is not a model. Does your model provide any explanation of why the price behaves the way it does?
2) One can calculate the parameters of the fit with time. You can add more and more data to the analysis and then calculate the parameters. You can show that the parameters converge to a stable value with time. As you have more and more data the model becomes stable and that is what the model is after 15 years of data. I made a prediction 5 years ago using the same model and my model is basically the same after 5 years.
Your parameters are not converging to a stable value. Specifically, your
n is not constant. It is falling over time. It was 5.9762 five years ago and it is 5.82 today. If you do the curve fitting for the first 5 years, I'm sure that
n will be greater than 5.9762, and I predict that in 5 years it will less than 5.82. How does your model explain that?
3) The usefulness of the models doesn't depend much at all on the parameters changing slightly.
Perhaps "useless" is an exaggeration. I say "useless" because it explains nothing. Furthermore, like all tools based solely on back-testing, the fact that your curve fits past data allows it to predict the past, but it says nothing about predicting the future.
Are you a physicist or an astronomer? I'm.
I tell you that in physics we make models all the time by simply fitting data. If you find a relationship between y and x that is a model. It is a mathematical model. Here the modelling assumes that the behavior of BTC is a power law. The R^2 shows that this mathematical model can explain 92 % of the behavior of BTC.
I gave you a link so you can learn about power laws and their significance in nature. Just discovering BTC is a power law is an incredible discovery that changes everything about the nature of BTC.
The title of the video is:
Why do Power Laws Work so Widely?
Watch it and then we can discuss maybe, you will learn something anyway. Here is again:
https://www.youtube.com/watch?v=HYQT9_ymsVYIf you listen to the video it is said over and over that physicists create models of power laws by fitting data. Most of these power laws are not understood in terms of what causes them (because these systems are so incredibly complex) even if there are some attempts to do that. Nobody knows exactly why metabolism rates in animals follow a power law but it is a model of how metabolism works and it can be used in biology to make a lot of interesting inferences.
When Kepler discovered the power law that governs the motion of the planet he didn't have any idea what caused that but it was not useless. It could be used to predict eclipses and other important things. They are called laws for a reason. Imagine you saying to him it was useless because it was just derived by fitting.
He had the idea of using logs which at that time was revolutionary. His discovery lead eventually Newton to find the law of gravitation. Yes, finding a deeper cause is what you do in the progression of understanding how a phenomenon works but it starts in making mathematical models of the process itself.
But one can learn a lot of things by knowing the system will behave in this way. It would be great to find out why BTC is a power law and what is the underlying cause but that is extremely difficult in the case of networks like BTC. Maybe eventually somebody will figure out, but they would have to start from recognizing it is a power law.
I made a prediction 5 years ago about BTC moving along a power law and this has been true since (in fact from the start of BTC history).
Again another person arguing with me that 5.94 is different from 5.82. IT IS NOT for god sake! Just people who have no clue on how statistical models are created will say that.
First of all the n value I calculated 5 years ago was just after a local peak and the outliers of the bubble skewed a bit the value, second the difference between the 2 predictions is insignificant for example with n = 5.94 we get after 5500 days that the nominal price is $62K with the value of n = 5.83 we get $59 K that is 3K difference, lol. Do you realize how stupid that remark is?
It doesn't matter much at all in particular given the entire idea is to focus on scale that is what we care is rounding to the next magnitude so even 80 or 90 are basically 100 in this exercise.
How do you know the parameters are not converging did you do the math? No.
Here is a graph on how exactly the parameter n is converging as you add more and more data. It is stabilizing. Most of the oscillations are actually due to the bubbles. One can eliminate them by using methods like RANSAC (look it up) and it will be even more stable. Here the graph showing how n is converging (going flat).
A power law model is all about understanding how long it will take to go up by a factor 10 and the model tells us BTC is a scale-invariant system and tells us exactly how long it will take.
Please watch the video, google power laws, and try to understand something if you care about BTC.
Also, this model allowed us to tell the bottom in November. I made public posts telling everybody we reached the bottom of $16K. Tell me again how useless this is.
Not just that but if somebody had used the model to buy at the bottom indicated by the area of discount in the chart and sold at the the areas of premium, even with an updated n (that is exactly what you do when you work with mathematical models, you update them with new data) you would have a strat with 99 % success rate and 950 profit factor (as I programmed it in Tradingview given it can only use past data when you do backtesting). USELESS?
LOL.
Why do you insist on discussing this with me as you want to teach me without having worked on these models of BTC since 2014? I do this for a living.
I don't get it.
Not sure why people come here and debate with somebody who has a Ph.D. in Physics and worked in science for 30 years, modelled BTC for 10 years, with such arrogance without understanding what they are talking about. I don't want to appeal to authority but if you discuss things you don't understand with a professional you should have a little bit more humility and be open to try to understand by asking questions instead of making useless claims.