How to Predict BMT Price Trends in Advance Using On-Chain Data?

On-chain data, as a core manifestation of blockchain transparency, provides a unique perspective for predicting the price trends of $BMT . Below are three key categories of on-chain indicators and their application methods:

1. Monitoring Exchange Fund Flows #Bubblemaps

By tracking the net inflow/outflow of BMT on centralized exchanges, one can assess changes in market supply and demand. For example, if significant net outflows occur on platforms like Binance (such as over 1 million BMT in a single day), it usually indicates that whales or institutions are accumulating tokens, which may signal a subsequent price increase; conversely, continuous net inflows suggest selling pressure risks. Combining tools like CryptoQuant can also help analyze the historical changes in exchange reserves to identify abnormal fluctuations.

2. Analysis of Holding Address Behavior

• Whale Movements: Changes in holdings of the top 100 addresses are important signals. If multiple whale addresses simultaneously increase their holdings and transfer to cold wallets, it often accompanies price rebounds, as was the case when whale holdings accounted for 42% shortly after BMT was listed in March 2025.

• Retail Investor Activity: A surge in the number of active addresses while prices remain stagnant may indicate a phase of accumulation by major players, requiring an analysis of holding duration distribution (HODL Waves) to determine the market cycle position.

3. On-Chain Governance and Ecological Activities @Bubblemaps.io

The voting participation rate and proposal direction on the Intel Desk platform for $BMT directly impact market sentiment. For instance, after the community approves a proposal for cross-chain functionality upgrades with a high vote count, prices often increase by 10%-15% within a week. Additionally, an increase in staking lock-up amounts (e.g., exceeding 20% of total supply) will also reduce circulation, boosting scarcity expectations.

Risk Warning: On-chain data should be assessed in conjunction with technical aspects (such as Bollinger Band breakouts) and macroeconomic conditions (like Federal Reserve policies) to avoid misjudgment based on a single indicator.