Maker Transactions

Available on: Solana, Ethereum, Base, Polygon, BSC, Blast, Avalanche, Arbitrum

Detecting Market Manipulation Through Trading Patterns

In the fast-paced crypto market, especially on Automated Market Maker (AMM) DEXes, genuine trading activity can be hard to distinguish from manipulation. The Participants / Transactions Ratio Checker looks beyond simple volume numbers, analyzing the nature and breadth of participation in trading activity to spot potential risks.

Analyzing Trading Dynamics

Understanding Participation vs. Volume

On AMMs, trading involves swapping tokens against a liquidity pool. Healthy markets typically exhibit a reasonable relationship between:

• Participation Breadth: The number of unique wallets interacting with the pool (e.g., initiating swaps).

• Transaction Volume: The total number of swaps occurring.

A significant disconnect—like extremely high transaction volume driven by relatively few unique participants—can signal unusual or potentially manipulative activity, such as wash trading.

How DIVINE Analyzes This Ratio

DIVINE intelligently assesses this relationship by considering the token's maturity:

• Age-Aware Analysis: The system recognizes that newly launched tokens often have different trading dynamics than established ones.

• Adaptive Standards: It applies tailored checks, using standards appropriate for the token's age (whether it's very new or has been trading for a while) when comparing participant numbers to transaction counts.

• Multi-Timeframe Checks: Analysis occurs over different periods (e.g., recent hours vs. the full day) using these age-appropriate standards.

• Ratio & Volume Monitoring: It flags tokens if the ratio of unique participants to total transactions is suspiciously low, or if transaction counts seem excessively high for a token of its age.

Why Adapt for Token Age?

New tokens might naturally have more volatile trading or fewer initial participants. By using adaptive standards:

• Fair Evaluation: We avoid unfairly flagging promising new tokens that are still finding their footing and building a user base.

• Accurate Detection: We can more effectively identify genuine manipulation signals relative to the token's lifecycle stage.

This nuanced approach provides a more reliable assessment than a one-size-fits-all check for AMM environments.

Manipulation Signals We Detect

Low Participant-to-Transaction Ratio

Healthy activity usually involves a relatively broad base of participants compared to the total number of swaps:

• Concentrated Activity: If the number of unique participants is abnormally low compared to the high volume of transactions (below the threshold for the token's age), it suggests activity might be concentrated among few wallets, raising a red flag.

• Consistent Health: Both short-term and longer-term trading activity should reflect a healthy participant-to-transaction relationship appropriate for the token's age.

Suspiciously High Transaction Volume

Excessive swap counts, especially when not matched by broad participation, can indicate artificial activity:

• Age-Relative Volume Caps: We check if the total number of swaps exceeds reasonable limits for a token based on how long it has been trading.

• Identifying Unusual Spikes: The system looks for abnormal surges in transaction counts compared to age-appropriate norms.

Why This Ratio Matters

Beyond Basic Volume Metrics

Simple volume figures don't tell the whole story on AMMs. Our analysis provides deeper insights:

• Quality of Activity: Helps determine if trading volume represents broad, genuine interest or potentially artificial inflation from limited sources.

• Sustainability: Assesses if price movements are supported by participation patterns appropriate for the token's age.

• Manipulation Risk: Highlights tokens where transaction volume seems disproportionately high compared to the breadth of participation, deviating from healthy, age-appropriate norms.

Real-World Protection

Analyzing the participant/transaction relationship helps protect against:

• Pump and Dumps: By identifying artificially inflated activity or volume generated by few actors.

• Wash Trading: By spotting scenarios where high volume comes from an unusually small number of participants.

• Misleading Activity: By validating that trading reflects reasonably broad participation.

The DIVINE Difference

While many tools focus on static code or liquidity checks, DIVINE delves into the dynamic behavior of the market on AMMs. The Participants / Transactions Ratio Checker intelligently adapts its analysis based on token age, offering insights into the quality of trading activity that static methods miss.

This sophisticated, age-aware check helps ensure that tokens with suspicious trading dynamics (like high volume from few participants) are flagged, providing a more robust layer of security and contributing to cleaner, more reliable signals in the AMM landscape.

"Volume shows how much is swapped, but the participant ratio reveals how many are swapping. Analyzing this based on age helps separate real market buzz from bot noise."