Traditional prediction models aren’t applicable to bitcoin and it’s cohort of degenerate and yet some very promising siblings.
How can they be? There is no cashflow, no balance sheets, no revenue and for many of the alt-coins out there, no product to review.
It shouldn’t come as a surprise than that traditional models of forecasting aren’t applicable to crypto and in many cases are as useless as a glass hammer.
So what to do?
Well, there are alternative models to look at and for the purpose of this article, let’s zero into just one.
The wisdom of the crowd model seems like a great alternative because it offers forecasters a way to gage market sentiment and understand which way the “proverbial market wind” is blowing.
But, before we decide that this model is the best possible way to peak into a crystal ball and leverage the predictions that this ball foresees, let’s instead do what scientists do and try to disprove the thesis.
Why isn’t the Wisdom of the Crowd model a good tool for predicting crypto price movements?
The moving target.
The Wisdom of the Crowd model has long been used in predicting certain events with verifiable outcomes (ones that don’t respond to influence). Think of game shows where the player gets to ask the audience to help find the right answer.
These things are well suited to be answered by the crowd because the answer is set in stone and all that the player is doing is surveying the audience to see which answer the majority of the audience sides with. However, applying the Wisdom of the Crowd model to predicting financial markets requires more patience.
Financial Markets are a 2nd Order Chaotic System.
If you’ve read Yuval Harari’s book Sapiens, you’ll know what the sub-headline alludes to, for the rest, a second level chaotic system, in it’s simplest definition, is a system (like the stock market) that responds to predictions.
In other words, when a prediction is made and put out into the public domain, depending on it’s weight, it will have an influence on the stocks trajectory (i.e. it may cause the predicted price to change).
Here’s an easy example for you to follow.
If I was a major influencer in the market (someone like a Goldman Sucks) and I put out a forecast saying that Bitcoin will be trading at $20,000 by the end of 2018, all the meanwhile bitcoin is hovering around $6,200 today (Sep-2018), would you not get in now and ride the bull to a gain of 217%.
Some of you may not be as easily influenced, however, considering that many will, it wouldn’t be too ridiculous to assume that the price of bitcoin will be driven up accordingly.
What else is strange is that this prediction, in a sense, became a self fulfilling prophecy, hence the market reacted to my prediction.
Last caveat before we move on to how the wisdom of the crowd model is applicable to predicting price movements in the crypto economy.
In the example above, I’ve stated my prediction for the end of the year in September. Assuming that my forecast had enough merit to drive the price up now, what happens in the next three months is anyones guess.
An area where the crowd excels is around identifying sentiment. Asking people to submit a forecast, in other words, is the same as asking them to take all their knowledge of a certain token as well as the market conditions and distill it into a single price prediction.
When you combine all the predictions and average them out, you get to see if the crowd is above or below the current price. This is the purest form of sentiment and while the prediction (or the average price) may not be accurate the general direction is.
I’ll leave you with a few notable sentences (below) that led us to develop KryptoLoop and leverage the crowds wisdom to help traders identify the truest form of market sentiment.
“A core assumption of market efficiency is that securities prices incorporate all price-sensitive information that is contained in historical prices. The usually tacit corollary is that price movements do not provide any guide to future prices, and hence markets have no predictive ability.
However, an implicit challenge to this assumption is the formal recognition that markets have momentum: that is, price moves in one direction tend to continue.
This is generally attributed to behavioral factors, namely, irrational biases in investor decisions ranging from herding and myopic trend following to under or over appreciation of the significance of new information.
By unpacking common finance assumptions, it is clear that any security’s price will move in line with the market’s expectation of risk and returns. In other words, security returns are determined by ex ante (based on forecasts) expectations of future cashflow, price and risk.
Prediction Markets — Les Coleman
All right folks I got to jet.
I love you,
Find me on Twitter under @iggsloop
Igor is a lover and a fighter. He happens to enjoy shitposting on crypto twitter and getting a beer with friends. His latest venture seeks to help traders improve their ROI through a crowd driven price prediction platform, called KryptoLoop. The Wisdom of the Crowd model they use mitigates most of the biases traders contend with and distills their collective knowledge into a single price prediction. It’s the best sentiment indicator a crypto trader can find and their predictions are within a tiny margin of error from actual price.