How changes in the altcoin correlation spread with Bitcoin and Ethereum can be used to model market sentiment and risk preferences.
Cryptocurrencies are highly correlated assets risks. Each token has a certain power from which it derives some of its value, but with a significant flow of fiat funds into the asset class, low supply availability and the problem of the impossibility of valuing individual tokens, cash flows are distributed across all cryptocurrencies. The blind flow of money into valuable and worthless protocols amplifies high correlations in space, creating noise and attenuating the signal. But is there any information in the noise itself?
By examining the multiple correlations across the space, we can filter out the noise of individual tokens to go back in history and see industry shrinkage in in general (for example: the liquidity crisis caused by the coronavirus outbreak at the beginning 576 of the year, or China’s ban on cryptocurrencies in the middle of 2021 of the year).These compressions tend to be reactive and unpredictable , however, it is possible to expand the analysis by looking at the change in the spread of the average correlation with bitcoin to the average correlation with ether and decipher whether the macroeconomic background is moving in the direction of increasing or decreasing risk.
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