NEAR +503.64% (Resonance Directional Strategy)

Reading time: 3 minAuthor: Team Resonance
NEAR +503.64% (Resonance Directional Strategy)

A breakdown of the NEAR trade using the cluster chart, volume analysis, and Resonance platform tools. We show how surplus, buyer weakness, and changes in price reaction to volume help identify a short entry point.

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Let’s break down a classic short entry setup on the NEAR coin.

After a strong impulsive rally, the market often continues to look “strong”: the buyer remains active, volume keeps going through, and price holds near the highs. At such moments, the cluster chart and volume analysis can reveal the first signs of trend weakening.

That is exactly the situation that formed on NEAR. After the asset gained roughly 40%, it began moving into a consolidation phase: buyer activity was still present, but its impact on price was gradually weakening.

The Resonance Screener was used to find this idea.

Entry reasons

Cluster chart: surplus formation

After the asset had risen by 40%, the move began to slow down. Active buying (red arrow) no longer led to new local highs (red line). This kind of activity pointed to the formation of a local surplus and increased the probability of a correction.

The coin moved into the third phase — consolidation (surplus). In this phase, buyer activity gradually weakens, while the move starts to slow down due to pressure from a limit seller.

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Dashboard: aggregated metrics

Price change per unit of volume:
The efficiency of market orders began to shift in favor of sellers (orange rectangle). This means that sell volume started to have a stronger impact on price than buy volume.

NEAR2.webp

Exit reasons

Cluster chart

The exit was executed at a 1:2 risk-to-reward ratio. After the decline, price began reacting to the reappearance of a buyer (green rectangle): market buying once again started leading to local upside movement (green arrow). That is why taking profits in this area was a justified decision.

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Conclusion

The trade made it possible to capture a move with a result of 503%.
The key idea in this scenario was the change in price behavior after the impulse. Despite continued buying, the asset stopped making new local highs, which pointed to surplus formation and the appearance of limit supply.
Additional confirmation came from the aggregated metrics: the efficiency of market orders began shifting toward the seller. It was precisely the combination of cluster analysis, volume assessment, and price reaction that made it possible to identify buyer weakness in advance and find a well-grounded short entry point.

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