Bitget and Nansen collaborate to empower traders with on-chain data to evaluate token potential

Bitget Research, the research arm of Bitget, the leading cryptocurrency exchange and Web3 company, has released its latest report in partnership with Nansen Research, the premier blockchain analytics platform, to unveil in-depth collaborative research on token-discovery strategies. This report aims to equip traders with essential insights and strategies for investing in early-stage and chain governance tokens.

 

By evaluating two sets of data correlated to token prices, Bitget and Nansen provide valuable insights. For early-stage tokens, the focus is on on-chain trading volume, community strength, technology, tokenomics, and security. For chain governance tokens with stable market caps, chain fees and Total Value Locked (TVL) are reliable predictors of prices. Additionally, social sentiment data from Nansen Discord shows a correlation with weekly token price movements, offering valuable investment insights.

 

Bitget and Nansen have joined forces to disclose the methodologies and metrics used to evaluate the potential of tokens at various stages. For early-stage tokens, the focus is on off-chain metrics and market traction, while established chain-governance tokens are assessed using on-chain leading metrics to forecast token prices.

 

Identifying promising early-stage tokens, or ‘hidden gems,’ is challenging due to limited on-chain data. Bitget assesses tokens based on market traction, including on-chain trading volume as relevant, to offer users opportunities to invest in high-potential projects. This meticulous listing process has driven Bitget’s significant user growth, with over 2.9 million new users in Q2 2024 and more than 180 tokens listed since April via its new products PoolX and Premarket.

 

Bitget’s token listing approach is focused on delivering maximum value with controlled risks. By prioritizing digital assets on the basis of their projected growth, the exchange lists them swiftly providing early access with a diverse range of tokens to its users. The evaluation process is based on quantitative standards and extensive research around assessing market traction, community sentiments, technological innovation, token economics and ecosystem security. The Bitget Research team utilizes an automated on-chain data monitoring system to identify trending tokens via its public activities, ensuring early access to its users through a reliable and efficient selection process.

 

“At Bitget, we position ourselves to balance between aggressive and conservative listing strategies. We prioritize listing legitimate, high-quality projects without missing lucrative opportunities. For instance, our research team identified PEPE due to its active on-chain data, and we listed it three weeks before the biggest CEX,” says Gracy Chen, Chief Executive Officer at Bitget.

 

“By combining our rigorous evaluation process with Nansen’s advanced on-chain and social media analysis, we aim to empower decentralized traders with the knowledge needed to make informed investment decisions in the ever-evolving cryptospace,” she added.

 

Nansen’s statistical analysis confirms TVL and Fees in ETH to be a significant predictor for price changes. Off-chain sentiment data from Nansen’s Alpha discord (premium members channel) shows correlation with weekly token price movements but with limited predictive power, showcasing the need for a multifaceted approach combining on-chain, off-chain and qualitative data for effective market analysis.

 

“Our collaboration with Bitget is a two-pronged approach to token evaluation. For promising early-stage tokens, Bitget focuses on community strength, security, and innovation. Meanwhile, Nansen’s expertise lies in on-chain data analysis, where metrics like TVL and fees have proven to be strong predictors of price movements for established tokens. While social sentiment remains a factor, analysis of on-chain and off-chain data offers a clearer picture of a project’s true potential,” said Aurelie Barthere, Research Analyst at Nansen.