#CriptoAlertas
How to measure Bitcoin dependency and risk
Step 1: Define the shock scenario
The analysis begins by selecting a plausible and high-impact Bitcoin event. This could involve defining a specific price shock, such as a 50% drop in BTC over 30 days, or a structural change, for example, Bitcoin's dominance falling from 60% to 40%.
Step 2: Quantify the dependency
The next step is to calculate the current Pearson correlation coefficient between ETH, XRP, and BTC. This statistical measure captures the linear relationship between the daily returns of the cryptocurrencies, providing a basis for the dependency. A value closer to +1 indicates that the altcoin is strongly linked to BTC's performance.
Step 3: Estimate the immediate price response
Using correlation data, apply regression analysis to calculate the beta (β) of each altcoin in relation to BTC. The beta coefficient estimates the expected price movement of the altcoin for each one-unit change in Bitcoin. This is similar to calculating the beta of a stock in relation to a benchmark index like the S&P 500 in traditional finance.
For example, if the β of ETH to BTC is 1.1 and the defined scenario assumes a 50% drop in BTC, the implied movement of ETH would be -55% (1.1 × -50%).
Step 4: Adjust for liquidity and structural risk
The adjustment requires going beyond the simple calculation of beta, considering key risks of the market structure. The order books of the cryptocurrency exchange with low depth must be analyzed to account for liquidity risk, while high open interest in derivatives should be assessed for structural risk and potential cascading liquidations.
