$LV Is Now Live as AnyCollateral — The Program's First Supported Asset
$LV is the first asset to go live under LeverUp's AnyCollateral program, with a 100% collateral ratio. Hold your LV. Keep your exposure. Use it as trading margin.
Product launches, integrations, and protocol updates from LeverUp.
14 articles
$LV is the first asset to go live under LeverUp's AnyCollateral program, with a 100% collateral ratio. Hold your LV. Keep your exposure. Use it as trading margin.
LeverUp positions and $LVMON staking are now trackable directly on MonadVision, powered by BlockVision's on-chain analytics.
Sixty days since LeverUp's protocol-level buyback and burn mechanism went live. Here's what the on-chain record shows.
As LeverUp continues to grow, we're taking steps to ensure our presence across major crypto data platforms
The whitelist period is over. Any wallet on Monad can stake LVMON and start earning — no allocation required.
Every listed stock perp on LeverUp now carries a single leverage ceiling: 100x. Tesla, Nvidia, MSTR — the full list, one tier. Here's what changed and why it matters.
LeverUp and DOKDO are running a joint trading campaign for the Korean community. $17,000 reward pool, rare Pokémon cards for the top 3, and a competitive PnL challenge — June 9 to June 30.
LeverUp and Nad.fun are launching two integrations together: LVMON as a pair token on Nad.fun V2, and graduated nad.fun tokens as candidates for the AnyCollateral Program. Here's what connects them.
Pingu is closing. LeverUp is welcoming Pingu traders with a one-month fee rebate program — 50% rebate on trading fees, up to $5,000 per wallet.
With Pyth Pro live on LeverUp, oracle feed freshness improved 19.5× — and the upgrade enabled protocol parameter changes that reduced trading fees by 57%.
LeverUp's AnyCollateral program lets holders of supported Monad tokens use them as trading margin — without selling, without tokenomics changes, without requiring project-side engineering integration.
LeverUp has switched to Pyth Pro, the institutional tier of the Pyth oracle network. Measured staleness dropped from 1.676 seconds to 0.086 seconds — a 19.5× improvement in feed freshness that flows directly to execution quality.
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