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In which case the validity of the accumulation model to supply is lost? The plan responds


PlanB, the creator of the Bitcoin-to-stock accumulation model, said in a recent statement emphasizing the validity of its price forecast model that the Bitcoin price would reach its forecast by the end of the year.

to the Report The Daily Hoodel, a Planbi, appeared on the podcast “What Bitcoin Did” and said he still believed in the accumulation model.

The accumulation-to-supply model is commonly used to predict the price of traditional assets, but Planby has released a special version of Bitcoin that predicts the price of this digital currency. According to the accumulation-supply model, the price can be predicted by the production rate of an asset.

Referring to the six-digit price of bitcoin by the end of 2021, Planby said:

I never doubted. I still think bitcoin by the end of the year [۲۰۲۱] Reaches a minimum price of $ 100,000. There is a lot of time left. We are currently in the $ 40,000 range, which is a 2.5-fold jump. We have experienced more climbs in the past; As a result, it is possible to have such an ascent now. I have a lot of confidence. I see on the internet that people are talking about $ 20,000 in bitcoin. I do not think that will happen. By Christmas, the price of bitcoin will reach $ 100,000.

According to Planby, this model is based on linear regression, in which the relationship between two variables is formed using a linear equation on the data; Thus, it can be “easily” determined when it loses its validity. “It simply came to our notice then.

This is just a linear regression, right? Therefore, it is clear exactly when this regression loses its validity.

In another part of his speech, he said:

According to the accumulation-to-supply model, after Hawing and the accumulation-to-supply rate increase, the price should also go up. So somehow we are waiting for this to happen; But when it stays low and fluctuates in the range of $ 20,000, $ 30,000, and $ 40,000 for years or months, it is clear that the line of this linear regression is no longer consistent with the data.

He added that it is very easy to detect a loss of credibility of the model and anyone can detect it.

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