Powerful Bitcoin Power Law Indicators

Adaptive Power Law Indicator

The BTC Power Law Model creates a linear fit by assuming a power law relationship between the Price and time (measured in days from the Genesis) block and therefore uses the log of the price and the log of time (that is rarely used in financial analysis) to perform the regression calculation. It turns out that this unusual but simple approach represents a surprisingl

Bitcoin Power Law Spiral Indicator

1) A power law trend that is adjusted to 2 standard deviations from the median Power Law trend.
2) A sinusoidal pulsating function that has a 4-year periodicity and is synchronized to the top of the first of the periodic BTC bubble.
3) An exponential decay fitted to the 3 observed bubbles to represent the empirical decay of the amplitude of these oscillations r

Advanced Power Law Bands Indicator
This oscillator is based on the previously published G. Santostasi Adaptive Power Law Indicator.
The Adaptive Power Law is different from other similar signals because it adapts to recent data and it continuous measure the best fitting line given different weight to present and past data so it has both the quality of detecting the general trend and adapting to r

Advanced Power Law Oscillator
The oscillator measures the difference between the current price and the Adaptive Power Law as a Percent Difference, as a Difference with the general trend in terms of Standard Deviations, or as an average between the price and the trend according to user preference.
It calculates also a Z score to assign a statistical value to each deviation. It color codes the magni

Bitcoin Power Law Hurst Coefficient
This is a special version of the Hurst Exponent. It is based on observing local power-law properties for Bitcoin. Using a moving window the spectrum of the price is calculated using wavelets and then the spectrum is fitted with a log-log graph (given it shows power law properties). The regression parameters are then used to calculate the Hurst coefficient. This

Power Law Liquidity Model  
When the price of Bitcoin is plotted against our global liquidity index, we observe a polynomial relationship. This model allows us to see when Bitcoin's price deviates significantly from the predicted value based on global liquidity:

Above the Model: When Bitcoin's price is above the polynomial fit, it indicates a potential lack of sufficient liquidity to support the c