Bitcoin Price in 2020 - Digital Asset Research

Bitcoin Price in 2020

Digital Asset Research, has released a new bitcoin price prediction model based on scarcity - that is. how much bitcoin is left to be mined? The model estimates that the price of Bitcoin can reach as high as $ 60,595 in May 2020, almost six times the current value of $ 10,670. This will place the Bitcoin market capitalization of almost $ 1.25 trillion.

This prediction model is based largely on extrapolating Bitcoin price performance before - into the future. Another key factor that according to the report will determine the price is the termination of the Bitcoin prize block - the next one will mature in 2020. Because the prize for the mining block is cut in half, the price of Bitcoin will rise.


While the report assumes that history will repeat almost perfectly, it does provide interesting insights into the behavior of Bitcoin in recent years. Digital Asset Research found that the price of Bitcoin tends to peak about one-third of its way through each prize cycle which is split in half - each peak beats the previous one. If this continues, this means that Bitcoin will find its maximum limit in September 2021 - beyond the $ 60,595 it quoted earlier. The report, however, does not speculate about what might be the upper limit of the price of bitcoin.

But clearly, this will require a large cash flow - maybe $ 1 trillion - to enter the market, to drive prices. Digital Asset Research speculates that it could come from investors who want to hedge the government's currency. Most people say that the US-China trade war or further geopolitical tensions in Hong Kong can drive investors towards Bitcoin. However, as we have seen recently when Dow Jones fell - money came out of the market, showing that Bitcoin might be seen as a riskier and more volatile asset than a safe place.

The prediction model was created using Bitcoin market data, which previously highlighted the relationship between the value of Bitcoin and its rarity. Digital Asset Research plans to revise the model when new information or market functions become clear, to improve accuracy over time.