TokensWAL/USDT
Day range: 0.03261—0.03505
WAL
Analysis context

WAL USDT

Walrus

Current price 0.0342 3.07% ↑
Summary by 4h WAL · price below EMA26 by 2.4% · RSI 43
Now WAIT
WAL forecast
Price 0.03412 4h · WAIT
EMA 26 / 50 0.03496 / 0.0365 price below EMA26 by 2.4%
Structure EMA200 0.03657 below EMA200 · EMA26 falling 1.32%
Bollinger 0.03278 - 0.0355 working range
RSI / ATR RSI 43 volatility 3.35%
Updating analysis data This will take a few seconds
Market wave
Market:
Tokens up —
EMA up —
Sample —
What matters now

Short summary for WAL

Scenario, levels and timeframe alignment.

63
Signal bias LONG bias

Buy 50% · Sell 25%

Context
Higher TF mixed
Lower TF LONG
Risk noise
Clarity Market argues

Dominant share 50%

Timeframe alignment

Timeframes disagree

15m LONG
1h LONG
4h Neutral
1d SHORT

SHORT prevails on the 4h and 1d timeframes, while the 15m and 1h timeframes more often point higher. Lower TF go against higher TF, so market entries are riskier than usual.

Our WAL signal statistics
Only closed signals, without guessing real user entries.
Closed-trade history History is building

WAL does not have enough closed trades for local statistics yet, but signals and the public feed are already available.

FeedSignals are live
StatisticsWill appear after closures
WAL has no closed trades in local statistics yet. You can view the public feed on the signals page.
36moderate
Token Risk

36/100

Quick check of tokenomics, liquidity and contract permissions.

Open risk passport
90d unlock 12.85%
Next unlock 02.11.2026
Circulating 52.35%
FDV / MC 1.91x
Quick take on WAL
Scenario, balance and statistics without extra technical noise.
LONG?

WAL is better approached with patience right now. Main reference: 4h, current scenario: "Better wait for confirmation".

Signal balance: buyers 50%, neutral 25%, sellers 25%. The current bias is on the buyer side, but entries should still be checked against the working timeframe. Timeframes: Timeframes disagree.

WAL trade history is still building, so current structure matters most now: scenario, signal balance and chart levels.

Reference: 4h Scenario: LONG? Buy 50% / Sell 25% History building
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WAL
WALWalrusProjected monthly release, cliff, projected from the circulating supply's own regular steps
Tokens53.54MValuation $1.83M
Supply4.28%Volume 2 966.57%
important
WAL
WALWalrusProjected monthly release, cliff, projected from the circulating supply's own regular steps
Tokens53.54MValuation $1.83M
Supply4.28%Volume 2 966.57%
important
WAL
WALWalrusProjected monthly release, cliff, projected from the circulating supply's own regular steps
Tokens53.54MValuation $1.83M
Supply4.28%Volume 2 966.57%
important
WAL
WALWalrusProjected monthly release, cliff, projected from the circulating supply's own regular steps
Tokens53.54MValuation $1.83M
Supply4.28%Volume 2 966.57%
important
About WAL

Walrus is a developer platform enabling data markets for the AI era, making data across all industries trustworthy, provable, monetizable, and secure. From AI agents to data markets and decentralized finance, Walrus empowers builders, users, and intelligent systems to control, verify, and create value from the world’s data.

Most of today’s data sits unused or untrusted, limiting the full potential of AI and digital economies. On Walrus, data isn’t just stored — it’s activated, powering new markets across every industry.

Developers can build efficient and resilient data markets where trust and value-creation are the norm. It provides developers with the essential tools needed to power a more trustworthy data economy, giving users and organizations the peace of mind to trust the accuracy of AI outputs and giving builders the power to create apps where sensitive data is safe.

As a result, data becomes more than just information, but the basis of new markets powered by Walrus. Users, as well as publishers and content creators, can monetize any kind of data. Researchers gain access to quality datasets to power discoveries. Companies can turn their data into new revenue streams, offset operational costs, and purchase new data to train the next generation of AI models