BMT = On-chain 'behavioral economics laboratory'
— it reveals data and explains the collective psychology and behavior patterns of market participants.
In traditional finance, markets are not always rational; behavioral economics studies human decision-making logic under irrational conditions.
In the blockchain world, BMT provides an unprecedented stage:
👉 It visualizes investor behavior trajectories, turning market psychology into observable experimental subjects.
Ⅰ, The 'psychological biases' behind on-chain data 🤯
Investors are often driven by psychology rather than purely rational judgment:
Herding effect: when one cluster buys, other wallets will follow.
Loss aversion: once large holders start selling, retail panic selling amplifies.
Anchoring effect: the wallet distribution of early holders becomes an anchor for market price expectations.
📊 Example:
Ⅱ, Bubblemaps: 'Developer' of behavior patterns 🧪
Bubblemaps' bubble chart not only shows capital distribution but also acts as a developer of behavior patterns:
Isolated bubbles: represent independent investors, less influenced by emotions;
Tight clusters: often indicate herd mentality or manipulating groups;
Cross-chain links: show arbitrage behavior or panic migration.
📊 Diagram:
Ⅲ, Intel Desk: 'Laboratory' of market psychology 🧑🔬
Intel Desk turns on-chain behavioral research into a group experiment:
Proposer raises the hypothesis: does a certain token have manipulation?
Voters allocate resources: does the community find this issue important?
Analysts provide data: to verify whether the hypothesis holds.
This is a decentralized 'behavioral economics experiment process.'
Ⅳ, Time travel: Historical cycles of behavior ⏳
One of the classic conclusions of behavioral economics is: humans repeat the same mistakes in different markets.
Bubblemaps' time-travel function provides on-chain evidence to validate this theory:
Early bull market: VC clusters sell high, retail investors take over;
End of bear market: large holders accumulate chips, market undervalued;
Repetitive cycles: behavior patterns replay across different tokens.
📊 Example:
Ⅴ, Cross-chain behavior: Global experiment 🌐
In the multi-chain ecosystem, different user groups exhibit different psychological characteristics:
Solana users: tend to short-term speculation, frequent capital migration;
BNB Chain users: more reliant on community consensus, showing stronger herd behavior;
Ethereum users: dominated by institutions and funds, tend to build positions rationally.
BMT puts these behavior patterns within the same experimental framework,
enabling researchers to compare the differences in 'psychological genes' across different chains.
📊 Comparison table:
Ⅵ, Trend prediction: behavior precedes price 📈
Price fluctuations are often the result of behavior patterns, not the cause.
Through BMT, we can capture behavioral signals before price changes:
Cluster capital inflow → precursor to price rise;
Large holder capital dispersion → beginning of risk release;
Large-scale cross-chain migration → systemic risk signal.
📊 Diagram:
Ⅶ, Conclusion: BMT = On-chain experimental field of behavioral economics 🎯
Behavioral research in traditional finance relies on questionnaires, simulations, and samples,
whereas in the blockchain world, all behaviors leave on-chain traces.
BMT provides not only a risk warning tool,
It is also the largest behavioral economics laboratory globally.
Data is real and tamper-proof;
Experiment participants cover the globe;
Research conclusions can be verified in real-time.
This means that BMT not only changes investors' toolbox,
but is more likely to change our understanding of the essence of financial markets.
