Topic: rpietila Wall Observer - the Quality TA Thread ;) - page 114. (Read 907212 times)

Yes, it seems that you have understanding on the subject, and also are probably doing quite well. It is difficult to try to distill the essence of quite long studies to an easily chewable form for people who do not understand the fundamentals of Bitcoin, nor of the model, while at the same time swimming in a sea of trolls.

I have no intention to waste my precious time more than is needed to rigorously prove to a nonexistent audience, why and how the model needs to be amended to take into accout the edge cases when it has turned the entire Earth into Bitcoins, nor what is my estimation of the probability that the model holds another year, nor what are the bounds for the model to "hold", nor many other things.

These are all important matters, but the capability of my audience to understand them and make informed decisions based on them any more than based on the "plain post" alone is just not there. If someone wants to buy bitcoin, my posting can help. If he does not want, he either cannot understand any deeper reasoning, or maybe he can, but his mind is made up nevertheless.

I posit the main problem is distribution, which is fundamental. Easy-of-use is just an implementation detail.

Wary, you find evidence of a log-logistic effect.

Love that avatar:

OK - so let's go through your list:

1. Fit to the data - here you have not really explained what did you try. I take your word that for all functions that you did exp was the best fitting - but I have the feeling that your imagination about the possibilities is limited.

2. Relation to  the observed mechanisms that produce the data - You don't mention any mechanism. You write that relation to time passing is better then relation to sun spots - cos(t) would also be related to time passing. A dumped oscillator function would actually have some relation to the observed mechanisms that produce the data - if we agree that people tend to predict that the price will go in the direction it goes now and that people predictions do influence the price.

3. Predicting future -
perl -e 'print 10**(-2.869800 + 0.003012 * 6000)'
1.59294213512763e+15

And that is a 1000 times more than all money supply on Earth (M0 is around 1.2e+12).

Evidently exp function cannot predict the future too far away and eventually it will have to be replaced by some S curve or maybe a dumped oscillator or something else. Maybe even something with a trigonometric function in it (the simplest oscillators)?

Hey, I don't want to personally attack you or anything... but, just for balance, that isn't a fallacy you can call anybody else on. If it is any consolation, at least you have a castle to console you past the loss of not being able to use fallacy #31 any more.

Oh... if that's what you were doing... calling fallacy on yourself... that's pretty funny.

Yes, I was about to write a post but as I realized that the content would have essentially been appealing to my own authority, since I have been right previously, I decided to delete the actual reasoning and just label the post "Appeal to authority."

WHAT?? THIS COMING FROM THE GUY THAT APPEALS TO HIS CASTLE IN ALMOST EVERY SINGLE POST AS THE REASON WHY PEOPLE SHOULD LISTEN TO HIM? WTF!!!!!!!!!!   

Agree. For example, it is reasonable to suggest that "pregnancy" is shorter for early adopters and longer for general population. Then it would be steep curve in the very beginning, then less and less steep later on. Something like this:



EDIT: It's real data

Fallacy #31: Appeal to authority.

Quants find a way to make a lot of money but do so a little bit at a time (arbitrage, hedging, etc.). I mean they can literally rob the average Joe's eyeballs out of their head on the trading circle. BUT, they suck at macro events. History tells us this. You are right, AnonyMint.

Will this be the big crash? Probably not. Will it take something fairly dramatic and currently unknown to pull us out of the downside channel? I think so. We're not hip, anymore.

The main problem is "ease of use"  -  for the general population it is too much trouble to buy bitcoins and use them. I see it all the time with people I know. But things are getting better. Services like coinbase and easier to use phone apps will help the general population move into bitcoin. Maybe it isn't happening as fast as Risto thought it would but once we get over this hump  the younger generation will jump on the wagon.

If we ever hit $5000/BTC... I give you legal ownership of my left kidney.

I like my kidneys... so what I am saying is that will never happen. Not next year. Not ever. Merry Christmas.

I could see $1500-$2000 in a bullish scenario.

Too many new players, too much regulatory bulls---, no Willy Bot, reduced black market presence, newbies getting Wall Street raped, etc., etc. Just because new adoption has, historically, been at a certain rate does not mean that this new adoption will continue out into the future. The baseline for the forecast is off.

It's, logically speaking, not terribly far off the rationale that banksters and credit agencies used in assigning inflated ratings to what were truly junk bonds -- the price of housing had not historically gone down and there had not been such a batch of foreclosures in prior history (and that sample size was much larger). However, the situation had changed... you had different people buying homes, different underwriting standards and down payment requirements, the perverse incentives created through securitization and derivatives, and balloon payments that functioned as a ticking time bomb.

Here, the dynamic that has changed is different, but the result is similar... adoption rates increased more dramatically when the price was still psychologically affordable. Now, simply having seen so many people profit, a lot of new users know that they are late to the game and that the odds are higher, now, that they'll be left holding a bag rather than profit. Tack on the fact that we went pop (moved away from black markets and towards regulation, taxation, and Wall Street) and have, resultantly, lost our hipness and appeal. Yea, this s--- is going down man. I'm not saying your math is wrong, but the application is off base.

Risto I trust common sense much more than short-term models and quants. Quants always fail eventually because as Armstrong points out their data sets do not encompass the long-tail events from a plurality of completed case histories going back 1000s of years.

That Bitcoin is not being used spontaneously by more people as they do facebook or viber should be a warning sign imo.

The upside price is certainly not finished. But is it really scaling to the general population (of which the vast majority are not investors)?

I am sure that you are trolling, yet want to explain the scientific method to others:

- The model needs to have a good fit to the data (best fit is usually best)
- The model needs to be in unison with the observed mechanisms that produce the data
- In absence of exact mechanisms (which is usually the case), the model should rely on general events (time passing) more than special (number of sunspots), if they give the fit that is equally good to explain the historical data.

- The model is used to predict the future. Therefore its future predictions have to be reasonable. In most other contexts, predicting a market cap of $17,000 billion dollars in 4 years is not credible. Here disregarding it as an impossibility may be a grave mistake, as it was to refuse to invest a few grand into Bitcoin 4 years back when it was available to all with little effort at $0.08. If Bitcoin has done something that other haven't, ever, it has a nonzero possibility of repeating the behaviour, and the model is better knowing it.

How about trigonometric functions? Have you tried them? Or polynomials with trigonometric functions? I am sure Excel have many many functions and you can combine them in many many ways - I am sure you have not tried them all. So my question is how do you chose your functions - why are you sure that exp is good and cos is not?

It is always, every day, the line (or other construct) that gives the highest R^2 fit with the USD/BTC price data between 2009-1-3 and present_day. For all the time it has been an exponential function, which is linear when plotted in logarithmic space as I do.



1. Not really. Others just don't come close. 2. That's quite theoretical, since I cannot convince myself that a model with more than 2nd degree term is anything but noise with no predictive power, and Excel allows construction to 6th degree, with no improvement in R^2.

What IS important is if the growth trend is slowing or not. I currently hold the opinion that the trend is pretty much intact and price is about to increase 10x in a year. AnonyMint thinks it has slowed.

If I am not mistaken, the best R-squared (least error from the data points) would be an N-degree polynomial for N data points such that the curve passes through every point.

Thus 'best fit' may have no correlation to predictive power.

The best fit is when you have a better R-squared value than any other fits. Excel calculates the best fits for every model automatically, so you can just conclude that a log-linear model has a better fit (0.94) than log-logistic (0.73).

kbm, I think you will find that Bitcoin did not accomodate that usage because it is a rich boys club and you can't play if you don't have real money. And the velocity of money is what drove the value of Doge (which is orthogonal to the creepy community that drove that velocity of money). My theory seems to be anecdotally verified by the Doge coin experience. The problem for Doge is it is just a small niche market and only one way of usage that doesn't appeal to wider audience, thus the market cap has scaled back accordingly also because the supply of cheap coins has been halving at a very accelerated rate and it is 91% mined out already. Doge provides one case study that my marketing concept may be true, but they made some big mistakes on the design (conceptually only a small niche and phasing out the debasement radically fast). The Doge target market is too narrow to synergize with the investor demographic—economies-of-scale are lacking.

Hmm - do you say that the line you are watching is not 'USD/BTC = exp(-2.869800 + 0.003012 * D), D being the number of days' anymore? Have you changed the coefficients or have you changed it altogether so some other function?

Your comment about only one best fitting trendline only makes sense if you constrain your search space - for example by choosing only exponential functions.

A side note - if you for example allow for trendlines to be polynomials of unrestricted degree - then you'd be able to fit the trendline to the price chart exactly (with no divergencies at all).

How can you assert that a fit with one model is lesser fit than a fit with another model? Define 'lesser'?