University Researchers Present Study on Daily Return and Liquidity in XRP

University researchers have unveiled an academic paper elaborating on the relationship between the return and liquidity of XRP and five other top-ranking cryptocurrencies.

These are researchers affiliated with HSBC Lab, China, and the School of Business and Management at Hong Kong University of Science and Technology, Hong Kong SAR, China.

The report highlighted the intricacies of the crypto market and stressed the importance of understanding the inter- and intra-asset dependencies among vital financial variables, specifically return and liquidity.

It focused on the daily return and liquidity data of Bitcoin (BTC), Ethereum (ETH), XRP, Binance Coin (BNB), Litecoin (LTC), and Dogecoin (DOGE).

According to the paper, the researcher selected the six assets due to their high market valuation, data availability, and diverse use cases.

It utilized data sourced from CoinMarketCap. The chosen timeframe spans 1,000 days, from March 6, 2020, to November 30, 2022.

This timeframe was deliberately selected to capture market dynamics during a period marked by significant fluctuations, including the impact of the COVID-19 pandemic on the global economy.

Notably, the researchers assessed liquidity using three low-frequency proxies. The computation of the three liquidity proxies involves utilizing daily open, high, low, and close prices.

The Research Finding

The researchers found that lower-tail dependencies are more prevalent in log returns. According to them, this aligns with the idea that crypto prices drop simultaneously during bearish markets, accompanied by decreased liquidity.

Also, the report noted BTC and ETH exhibit strong interdependence in log returns and all liquidity proxies. Similarly, LTC and DOGE demonstrated strong correlations with BTC in terms of both liquidity measures and log returns.

On the other hand, XRP displayed very strong correlations with LTC and weaker correlations with other coins.

According to the report, ETH notably exhibited high correlations with BTC, BNB, and LTC. It also mentioned that ETH demonstrated the highest correlation to the market among the six selected cryptocurrencies. In contrast, DOGE displayed the lowest correlation.

Meanwhile, weak symmetric correlations were found in other crypto pairs, including ETH-DOGE, BTC-XRP, XRP-BNB, XRP-DOGE, BNB-DOGE, and BNB-LTC.

Ultimately, the analysis reveals robust cross-asset lower-tail dependence in return and significant cross-asset upper-tail dependence in illiquidity measures. This dependence is particularly pronounced in specific cryptocurrency pairs, notably Bitcoin, Ethereum, and Litecoin.

Additionally, the study observes that returns tend to be higher when liquidity is lower in the cryptocurrency market.

According to the researchers, the findings carry substantial implications for various aspects, including portfolio diversification, risk management, and developing trading strategies for traders.

Furthermore, they argue the insights from this study could inform regulatory policy-making for regulators overseeing cryptocurrencies.

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