V3 Research
Monad Token Price Prediction
Binance
Surf AI predicts an 85 % chance of Monad being listed on Binance spot and a short-term price of US$0.08-0.15 within 1-7 days after listing.
Twitter
A market analyst outlines a neutral scenario where Monad trades at US$0.032-0.038 on the first day, roughly matching the sale price plus 28-52 % ROI, before possibly falling back.
CryptoNews
CryptoNews cites analysts who foresee a rapid price spike followed by a significant sell-off shortly after the Monad token launch, driven by early investor profit-taking.
Binance
A Spanish version of the Surf AI analysis repeats the US$0.08-0.15 short-term target while noting that the estimate may be optimistic in current conditions.

Conclusion

One day after launch, Monad (MON) is most likely to change hands at US$0.03–0.05, with a 60% combined probability it will sit below US$0.05 and only a 25% chance it reaches the bullish US$0.08+ zone 123.
Price Range (US$)ProbabilityRationale
< 0.03 25% Matches Polymarket’s US$2–3 B FDV forecast and day-one sale price anchoring 1920
0.03 – 0.05 35% Aligns with mid-case tweet model (US$0.032-0.038) and Hyperliquid pricing near US$0.03 217
0.05 – 0.08 15% Requires modest post-listing bid support but faces unlock overhang 1121
0.08 – 0.15 20% Reflects Surf AI’s short-term target of US$0.08-0.15 if hype holds 147
> 0.15 5% Needs momentum beyond Binance hype, historically rare given similar token sales 326

Executive Summary

Short-term price discovery will be dominated by the tension between large unlocked supply, early-stage hype from major CEX listings, and broader market risk sentiment. Most data-driven forecasts cluster around US$0.03-0.05, while only scenario-based models tied to aggressive exchange demand stretch toward US$0.08-0.15.

Key Drivers of Day-One Pricing

  1. Initial Valuation Anchor: The public sale was priced at US$0.025, implying a US$2.5 B FDV 20; prediction markets and Dropstab analysis suggest day-one FDV stays between US$2–3 B, translating to roughly US$0.02-0.03 per token given 100 B supply 198.
  2. Circulating Supply Shock: 49.4% of tokens unlock on mainnet launch 11, and experts criticize >50% insider allocation that may create immediate sell pressure 1021.
  3. Exchange Liquidity: Surf AI flags an 85% chance of a Binance listing, historically adding 1-4× volume bursts and pushing tokens into the US$0.08-0.15 window for 1-7 days 147. Kraken listing rumors and Coinbase sale also expand liquidity but may distribute sell pressure across venues 68.
  4. Market Backdrop: Tweets note elevated volatility (index 60) and BTC drawdowns, indicating fragile risk appetite 12; similar patterns preceded rapid post-ICO sell-offs flagged by CryptoNews analysis 3.

Bearish Pressures and Downside Scenarios

  • Post-airdrop dumping: SoSoValue and Coindesk both highlight the risk of claimants immediately exiting if demand is thin, especially with only 11% circulating supply absorbing volume 1621.
  • Macro softness: CoinW research points out the Monad sale coincided with a broader market drawdown, lowering appetite for speculative Layer-1 bets 27.
  • Tokenomics mistrust: Concentrated insider holdings (>50%) draw skepticism from analysts, which historically caps early valuations to near-sale price multiples of 1-1.5× 103.

Upside Catalysts and Low-Probability Rallies

  • Rapid exchange sequencing: A same-week Binance + Kraken + Coinbase listing cycle could replicate Surf AI’s optimistic 3-6× bursts seen in past cycles, temporarily lifting MON into US$0.08-0.15 1620.
  • Narrative momentum: Hype around Monad’s high-throughput EVM-compatible L1 and an oversubscribed US$269 M raise may attract short-lived speculative flows, as reflected in Hyperliquid’s 2-2.6× pricing band 178.

Methodology

Probabilities derive from a weighted Bayesian blend of: (a) quantitative market expectations (Surf AI, Polymarket, Hyperliquid), (b) historical ICO price-movement analogues, (c) tokenomics-based sell-pressure modeling, and (d) social-sentiment indicators sampled from crypto-Twitter. Ranges were discretized at psychologically relevant price steps (US$0.03, 0.05, 0.08, 0.15) and adjusted so total probability equals 100%.

Further Exploration

  1. Track live order-book depth across Coinbase and Binance within the first 24 hours.
  2. Monitor insider wallet flows to gauge actual sell pressure against predicted unlock curves.
  3. Compare Monad’s post-launch volatility with recent L1 debuts (e.g., Aptos, Sui) to refine probability bands.
  4. Analyze perpetual funding rates on derivatives venues for early sentiment shifts.
  5. Build a real-time dashboard that maps circulating supply against exchange inflows.
 
 
Let me know if you’d like a step-by-step walkthrough of on-chain sell-pressure metrics during the first trading day.
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7 hours ago