GugaOnChain

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GugaOnChain

GugaOnChain

@GugaOnChain

🏅 Verified Author for @cryptoquant_com | 💡 Insights: BTC / On-chain, Technical and Macro Analysis

Rio de Janeiro, Brazil Katılım Ekim 2025
150 Takip Edilen123 Takipçiler
GugaOnChain
GugaOnChain@GugaOnChain·
cryptoquant.com/quicktake/69bc… Retail panicked over the drop to $69.4K due to war tensions in the Middle East and oil at $116. What did 'Smart Money' do? They bought your despair and have already pushed the price back to $70,439. $BTC
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CryptoQuant.com
CryptoQuant.com@cryptoquant_com·
Despite fears of high interest rates, a $199 million inflow into ETFs and strong spot demand sustained Bitcoin above the $74K mark. – By @GugaOnChain
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Julio Moreno
Julio Moreno@jjcmoreno·
The Bitcoin power law model looks good, but is flawed. The relationship between price and time is spurious (fake). I'll explain below. 1. The model is flawed because it does't account for autocorrelation. You can see this in the regression results, particularly in the Durbin-Watson statistic (red rectangle). It should be 2 for autocorrelation not to be present, but it's basically zero (high positive autocorrelation). Autocorrelation violates one of the key assumptions of linear regression. It doesn't matter that the R-squared is high (orange rectangle), the high R-squared is explained by the autocorrelation. The model has also other problems (blue, yellow and green rectangles) that also violate some of the assumptions of linear regression (normal distribution, etc). 2. The price of Bitcoin is autocorrelated, meaning that past data helps explain the current price, this is very common in time series analysis. You can see this in the next chart (bars outside the shaded area). 3. Power law models seem to explain well some relationships, but this is for analysis that doesn't involve time (time series). I took this chart from @dotkrueger
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