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In the next subsection, these results are confronted with the second quarter of 2019. Only Decred (DRC) exhibited its highest correlation coefficient with Bitcoin (0.82). Among all cryptoassets investigated, most of them displayed their highest correlation coefficients with Ethereum.

#PROOFS KEYBASE CODE#

While Stellar was initially built on the Ripple protocol, its code was forked and quickly revised. XRP remains highly correlated with Stellar (0.80), in line with findings from our past report about cluster analysis.HT (Huobi Token) has its highest correlation coefficient (0.69) with BNB.Even though Ethereum (ETH) displayed the most substantial correlations with most of the investigated cryptoassets, ETH exhibited a relatively low correlation with Ethereum Classic (ETC), with a correlation coefficient of 0.69.Ultimately, a few correlations are worth mentioning explicitly: Specifically, additional asset-specific factors may have existed with LEO and (CRO) being almost uncorrelated to all other cryptoassets. LEO, (CRO), and Huobi Token (HT) were less correlated on average with other cryptoassets. “Binance Effect”: assets listed on Binance displayed higher correlations than with the cryptoassets not listed on Binance.However, Ethereum is presumably transitioning to PoS -in the near future-, and it remains to be seen whether it would impact the strength of its correlation with Bitcoin. For instance, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Bitcoin Cash (BCH), and Bitcoin SV (BSV) displayed an extremely high median (above 0.75).

Proof of Work assets exhibited a larger correlation with each other.

In a similar fashion to our previous reports, several factors influence the strengths of these relationships, such as: For instance, Ethereum (ETH) and Bitcoin (BTC) displayed a correlation coefficient of 0.81 over the third quarter of 2019.

Finally, Ethereum (ETH) became the most correlated cryptoasset in the ecosystem, conceivably turning it into one of its principal benchmarks.īased on the above chart, correlations between all pairs are always positive and typically more significant amongst the largest cryptoassets.

Following their respective listings, Dogecoin (DOGE) or Cosmos (ATOM) average correlation increased in Q3 2019.

“Binance Effect”: assets listed on Binance displayed greater correlations than with the cryptoassets not listed on Binance.

Programmable blockchains (e.g., NEO, Ethereum, EOS) exhibited, on average, higher correlations with each other than with non-programmable assets.

Privacy effect: Dash (DASH), ZCoin (ZEC), and Monero (XMR) displayed higher correlations than with other cryptoassets.

Proof of Work assets tended to exhibit a more substantial correlation with each other.

Several factors influence the intensities of these relationships:.

In Q3 2019, the top large-cap assets displayed higher positive correlations than in the second quarter of 2019.

In comparison, BTC trading dominance fluctuated around 15-25% for the first half of 2019. Conversely, Bitcoin trading dominance appears to be at local highs, with more than 40% of the trading activity on Binance being on BTC against stablecoins pairs. Over the third quarter of 2019, Bitcoin marketcap dominance kept increasing, temporarily reaching new highs exceeding 70%.Meanwhile, large marketcap altcoins all displayed negative price performances ranging from -38% to -60%. In Q3, Bitcoin price dropped by nearly -30%, closing on September 30th at around $8,000. The third quarter of 2019 exhibited adverse price movements, breaking the two consecutive quarterly price gains in Q1 and Q2.

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