Crypto-assets heavily influenced by market changes due to positive correlation statistics

  • 06 July 2019, Saturday, 16:00

In the cryptocurrency industry, exchanges form the backbone of the entire ecosystem. Major exchanges often impact the prices of virtual assets, as it is essential for digital currencies to be available on these crypto-institutions.

Exchanges have had an impact in almost all sectors; from Binance promoting IEO projects like Harmony.One and Fetch.AI, to the launch of margin trading and futures trading.

Binance recently released its 2019 Quarterly Crypto-Correlation report, which concluded that the crypto-industry had recorded a fairly lucrative Q2 in 2019.

The report extensively spoke about the correlation between virtual assets. According to the report, whenever the existing correlation between assets is above 0.5 or below -0.5, it is said to have strong or negative correlations. In the case of a positive correlation, the risk implied between digital currencies is the same as they tend to move in the same direction when the market changes. When a negative correlation is achieved, it means that one asset can be used as a hedge against the other, when the market is volatile.

According to the report, a majority of the coins shared positive correlations with each other as most of the pairs projected a score of 0.5 or more. It was also observed that none of the pairs exhibited negative correlation.

The report added that a range of distinct factors had only a minor effect on coins’ performances in the market.

Tezos [XTZ], Dogecoin [DOGE] and Bitcoin SV [BSV] projected very low correlation with the rest of the cryptocurrency market

In contrast, XRP and XLM shared an extremely high correlation between them, which was up to 0.87. XRP and XLM are competititors and strive to improve the global remittance industry. Hence, it was not surprising that the tokens shared a higher positive correlation.

The report concluded with the fact that major crypto-assets were behaving in consonance with the bull run of 2017, which essentially suggested that the correlation factor had not changed over time.