Dynamic Burn Economics & Scarcity Simulation Model

Sudo’s tokenomics are built on aggressive, real-time burning mechanisms that ensure permanent scarcity while continuously driving upward price pressure. This section models the potential deflationary impact of Sudo’s economic design under projected adoption and activity scenarios.

1. Key Burn Mechanisms Recap

The SUDO token’s deflationary pressure comes from multiple burn triggers tied directly to platform usage:

• Hourly Auto-Buy from Revenue: Every hour, $10 worth of SUDO is purchased from the market; 70% ($7) is permanently burned.

• Username Purchases: Premium usernames cost $1–$10, with 100% of the payment converted to SUDO and burned.

• Smart Contract Channel Integrations: Linking a verified smart contract to a group or channel requires a $10 fee, 100% burned.

• MiniApp and Bot Activation Fees: Fees for deploying or activating MiniApps/Bots burn between 50% and 100% of the amount paid, depending on developer settings.

• Token Sell Penalty (Future Feature): A percentage of tokens sold could be burned to discourage dumping and maintain price stability.

2. Burn Simulation Model (Base Case)

Assumptions:

• 10,000 premium usernames purchased annually at an average of $5 each = $50,000 burned.

• 10,000 smart contract integrations at $10 each = $100,000 burned.

• Hourly auto-buy: $10 × 24 hours × 365 days = $87,600 in buys, with 70% ($61,320) burned.

Total Yearly Burn: $61,320 (hourly) + $50,000 (usernames) + $100,000 (contract integrations) = $211,320 burned annually.

3. Burn Impact on Token Supply

With an initial supply of 100,000,000 SUDO, burns reduce the circulating supply significantly year-over-year.

• Year 1: ~21.13M tokens burned (avg $0.01/token) → Remaining supply: ~78.87M

• Year 2: ~17.5M tokens burned → Remaining supply: ~61.37M

• Year 3: ~14M tokens burned → Remaining supply: ~47.37M

• Year 4: ~11M tokens burned → Remaining supply: ~36.37M

• Year 5: ~8M tokens burned → Remaining supply: ~28.37M

Note: Burn volumes naturally decline over time as token prices rise, since each dollar buys fewer tokens. However, the percentage of circulating supply removed remains significant.

4. Scarcity-Driven Price Model

Using a constant-demand AMM (x × y = k) model:

• Initial Liquidity Pool: 10,000,000 SUDO paired with 10,000 USDT.

• Liquidity Burned: 90% of LP is destroyed at launch, leaving 1,000,000 SUDO in circulating LP.

• Hourly Buys: $10/hour = 8,760 buy events per year.

Sample Price Growth Projection (Under Active Burn):

• Launch Price: $0.0010 (1.0x)

• 1 Month: ~$0.0015 (1.5x)

• 6 Months: ~$0.0055 (5.5x)

• 12 Months: ~$0.015–$0.030 (15–30x)

• 24 Months: ~$0.10–$0.25 (100–250x)

• 3–4 Years: >$0.50 (500x+)

Drivers of Price Growth: Swap frequency, LP depth, token availability in pools, and accelerating user activity.

5. Conclusions

• Aggressive Hourly Burn + Limited LP = Extreme Scarcity: The combined effect of constant hourly burns and a small, locked liquidity pool amplifies price impact.

• Multi-Source Demand: Messaging, MiniApps, usernames, and contract sync fees all drive direct SUDO purchases from the market.

• Non-Linear Price Growth: As burns compound and supply shrinks, price growth accelerates beyond linear models.

• User Growth Feedback Loop: More users → more burns → higher scarcity → higher price → more adoption.