Investor Guide

INVESTMENT DISCLAIMER

This documentation is for informational purposes only and does not constitute investment advice, financial advice, trading advice, or any other sort of advice.

• No Endorsement: Hokusai Protocol does NOT endorse investment in any specific model tokens. Each token represents an independent project with unique risks.
• High Risk: Token investments are highly speculative and risky. You can lose 100% of your invested funds. Never invest more than you can afford to lose.
• Do Your Own Research: Nothing in this documentation should be taken for granted. You must independently verify all claims, contract addresses, team credentials, and technical details before investing.
• No Guarantees: Past performance does not guarantee future results. API revenue, model performance, and token prices can change dramatically.
• Regulatory Risk: Token regulations vary by jurisdiction. Ensure compliance with your local laws before participating.

BY PROCEEDING, YOU ACKNOWLEDGE THAT YOU UNDERSTAND THESE RISKS AND ACCEPT FULL RESPONSIBILITY FOR YOUR INVESTMENT DECISIONS.

This guide helps investors understand how to evaluate Hokusai model tokens and the associated risks. Whether you're researching your first token or evaluating multiple projects, this guide covers due diligence, risk assessment, and informed decision-making.

Who is This Guide For?

This guide is for investors who want to:

• Participate in model token launches
• Support promising AI models
• Gain exposure to AI model performance
• Trade tokens on the bonding curve AMM
• Understand risk/reward dynamics

You should read this if you are:

• New to Hokusai protocol
• Considering investing in a model token
• Planning to participate in a seven-day launch
• Looking to trade existing model tokens

Investment Thesis

Why Invest in Model Tokens?

Hokusai model tokens represent a new asset class backed by AI model performance and usage:

Value Drivers:

1. Performance Improvements → More tokens minted → Rewards distributed
2. API Usage → Revenue generated → Fees deposited to reserves → Price increases
3. Supply Dynamics → Burning for access → Deflationary pressure
4. Network Effects → More usage → More fees → Higher token value

Comparison to Traditional Assets:

Feature	Hokusai Model Token	Startup Equity	Public Stock	Cryptocurrency
Backing	USDC reserves + API revenue	Company assets	Company assets	Protocol value
Cash Flow	20% API fees → reserves	Variable	Dividends	Variable
Liquidity	Always (AMM)	Illiquid	Market hours	24/7
Exit Strategy	Sell anytime (after Day 7)	Acquisition/IPO	Sell anytime	Sell anytime
Price Discovery	CRR formula	Valuation rounds	Market price	Market price
Governance	Token votes	Shareholder votes	Shareholder votes	Variable
Volatility	High	Very High	Medium	Very High
Minimum Investment	Any amount	$10k-100k+	Any amount	Any amount

Risk-Return Profile

Expected Return
     ↑
High |     🚀 Successful Model
     |        /
Med  |      /    📊 Average Model
     |    /
Low  |  /___________❌ Failed Model
     |________________→
        Low   Med   High   Risk

High Return Potential:

• Early successful models: 10-100x returns
• Strong API usage: 2-5x sustained growth
• Network effects: Long-term value accrual

High Risk Reality:

• Model underperformance: -50-90% losses
• Post-launch selling: -30-50% volatility
• Smart contract risks: Total loss possible
• Low liquidity: Hard to exit large positions

Investment Process

Step 1: Research Models

Before investing, thoroughly evaluate the model:

Performance Metrics:

☐ Current accuracy/performance score
☐ Historical improvement trajectory
☐ Benchmark comparisons (vs competitors)
☐ DeltaOne generation rate
☐ Contribution activity and frequency

Team Assessment:

☐ Developer reputation and track record
☐ Model documentation quality
☐ Community engagement level
☐ Transparency and communication
☐ Technical expertise demonstrated

Tokenomics Analysis:

☐ Initial supply and distribution
☐ Reserve Ratio (CRR) setting
☐ Trade and protocol fees
☐ Projected API usage and revenue
☐ Token minting schedule

Market Opportunity:

☐ Problem being solved
☐ Target market size
☐ Competitive landscape
☐ Adoption potential
☐ Revenue model clarity

Step 2: Analyze Launch Parameters

Every model launches with specific AMM parameters:

Check Initial Conditions:

// Connect to AMM contract
const amm = await ethers.getContractAt("HokusaiAMM", ammAddress);

// Get key parameters
const reserveRatio = await amm.reserveRatio(); // CRR (w)
const tradeFee = await amm.tradeFee(); // e.g., 0.25%
const protocolFee = await amm.protocolFee(); // e.g., 5%
const buyOnlyUntil = await amm.buyOnlyUntil(); // Launch end time

// Get initial state
const reserve = await amm.getReserve();
const supply = await amm.getTotalSupply();
const price = await amm.spotPrice();

console.log(`Initial Price: ${ethers.formatUnits(price, 18)} USDC`);
console.log(`Reserve Ratio: ${reserveRatio / 1e16}%`);
console.log(`Initial Reserve: ${ethers.formatUnits(reserve, 6)} USDC`);

Evaluate Launch Setup:

Parameter	Conservative	Moderate	Aggressive
CRR (w)	35-50%	20-35%	5-20%
Initial Reserve	$50k+	$10-50k	$1-10k
Initial Supply	500k-1M	1-5M	5-10M+
Initial Price	$0.10+	$0.01-0.10	$0.001-0.01

Red Flags:

• ❌ CRR < 10% (too volatile)
• ❌ Initial reserve < $1,000 (too thin)
• ❌ No initial supply (nothing to buy)
• ❌ Fees > 5% (too extractive)

Step 3: Plan Your Investment

Determine Position Size:

Portfolio Allocation Guidelines:

High Risk Tolerance (Crypto-native):
- Single model: 2-10% of portfolio
- Multiple models: 15-30% total
- Position per model: $1k-50k

Medium Risk Tolerance (Diversified):
- Single model: 0.5-2% of portfolio
- Multiple models: 5-15% total
- Position per model: $500-10k

Low Risk Tolerance (Conservative):
- Single model: 0.1-0.5% of portfolio
- Multiple models: 1-5% total
- Position per model: $100-1k

Choose Investment Strategy:

Strategy A: Early Momentum

Allocation: Front-load 70% on Days 0-1
Rationale: Capture lowest prices
Risk: High if launch fails
Best for: High conviction + risk tolerance

Strategy B: Dollar-Cost Average

Allocation: Equal amounts Days 0, 2, 4, 6
Rationale: Average in, reduce timing risk
Risk: Medium, miss some early gains
Best for: Moderate conviction

Strategy C: Wait and See

Allocation: 30% Days 0-3, 70% Days 4-6
Rationale: Observe momentum first
Risk: Lower, but higher avg price
Best for: Lower conviction, cautious

Strategy D: Post-Launch Entry

Allocation: 0% during launch, buy Day 8+
Rationale: Avoid launch volatility
Risk: Lower, but miss launch gains
Best for: Very cautious, patient

Step 4: Execute Trades

Setup Requirements:

1. Crypto wallet (MetaMask, Rabby, etc.)
2. USDC on same chain as model
3. Native token for gas (ETH, etc.)
4. Access to model's AMM contract

Buying During Launch:

// 1. Approve USDC spending
const usdc = await ethers.getContractAt("IERC20", USDC_ADDRESS);
const approvalAmount = ethers.parseUnits("10000", 6); // 10k USDC
await usdc.approve(ammAddress, approvalAmount);

// 2. Get buy quote
const usdcAmount = ethers.parseUnits("1000", 6); // $1000
const tokensOut = await amm.getBuyQuote(usdcAmount);
console.log(`Quote: ${ethers.formatUnits(tokensOut, 18)} tokens for $1000`);

// 3. Set slippage tolerance (e.g., 2%)
const minTokens = tokensOut * 98n / 100n;

// 4. Set deadline (5 minutes)
const deadline = Math.floor(Date.now() / 1000) + 300;

// 5. Execute buy
const tx = await amm.buy(minTokens, deadline, { value: usdcAmount });
await tx.wait();
console.log("Purchase complete!");

Pro Tips:

• ✅ Buy during low activity (late night UTC)
• ✅ Monitor gas prices, buy when low
• ✅ Split large orders (< 5% of reserve)
• ✅ Keep records for tax purposes
• ⚠️ Never invest more than you can afford to lose

Step 5: Monitor Your Investment

Daily Monitoring (Days 0-7):

☐ Check reserve growth
☐ Monitor buy activity
☐ Track price changes
☐ Read team updates
☐ Assess community sentiment

Weekly Monitoring (Post-launch):

☐ Review API usage metrics
☐ Check fee deposits to reserves
☐ Monitor token minting events
☐ Track trading volume
☐ Re-evaluate thesis

Tools and Resources:

// Create monitoring dashboard
async function getModelMetrics(ammAddress) {
    const amm = await ethers.getContractAt("HokusaiAMM", ammAddress);

    const reserve = await amm.getReserve();
    const supply = await amm.getTotalSupply();
    const price = await amm.spotPrice();
    const reserveRatio = await amm.reserveRatio();

    const marketCap = (price * supply) / BigInt(1e18);
    const tvl = reserve;

    return {
        price: ethers.formatUnits(price, 18),
        reserve: ethers.formatUnits(reserve, 6),
        supply: ethers.formatUnits(supply, 18),
        marketCap: ethers.formatUnits(marketCap, 6),
        tvl: ethers.formatUnits(tvl, 6),
        reserveRatio: Number(reserveRatio) / 1e16
    };
}

Exit Strategies

When to Sell

Profit-Taking Scenarios:

Take Profits at +100% (Conservative):

Entry: $1,000 → Now worth $2,000
Action: Sell $1,000 (50%), hold rest
Result: Original capital back + house money

Take Profits at +200-500% (Moderate):

Entry: $1,000 → Now worth $3,000-6,000
Action: Sell 50-70%, hold rest
Result: Significant profit secured

Hold for Moon (Aggressive):

Entry: $1,000 → Now worth $5,000+
Action: Hold until +1000% or failure
Result: Max gains or max pain

Stop-Loss Scenarios:

Protect Capital at -30%:

Entry: $1,000 → Now worth $700
Action: Sell all, cut losses
Rationale: Model not performing

Reassess at -50%:

Entry: $1,000 → Now worth $500
Question: Has thesis changed?
- If yes: Sell remaining
- If no: Hold or average down

How to Sell

Post-Launch Only (Day 7+):

// 1. Verify bonding round ended
const isBuyOnly = await amm.isBuyOnlyPeriod();
if (isBuyOnly) {
    throw new Error("Cannot sell during bonding round");
}

// 2. Get sell quote
const tokenAmount = ethers.parseUnits("1000", 18);
const usdcOut = await amm.getSellQuote(tokenAmount);
console.log(`Quote: ${ethers.formatUnits(usdcOut, 6)} USDC for 1000 tokens`);

// 3. Approve tokens
const token = await ethers.getContractAt("IERC20", TOKEN_ADDRESS);
await token.approve(ammAddress, tokenAmount);

// 4. Set slippage (e.g., 3% for volatile periods)
const minUSDC = usdcOut * 97n / 100n;

// 5. Set deadline
const deadline = Math.floor(Date.now() / 1000) + 300;

// 6. Execute sell
const tx = await amm.sell(tokenAmount, minUSDC, deadline);
await tx.wait();
console.log("Sale complete!");

Timing Considerations:

• ⏰ Best time: After fee deposits (higher price)
• ⏰ Avoid: Right after Day 7 (high volatility)
• ⏰ Consider: Tax implications (short vs long term)
• ⏰ Plan: Stagger sells if large position

Risk Management

Diversification

Don't Put All Eggs in One Basket:

Example $10k Portfolio:

High Risk (Crypto-Native):
- 3-5 model tokens: $2k each
- Keep 20% stablecoins for opportunities

Medium Risk (Balanced):
- 5-8 model tokens: $1-1.5k each
- Keep 30% stablecoins

Low Risk (Conservative):
- 8-10 model tokens: $500-1k each
- Keep 50% stablecoins

Diversification Criteria:

☐ Different model types (NLP, vision, etc.)
☐ Different stages (launch vs mature)
☐ Different CRR levels (volatile vs stable)
☐ Different teams/developers
☐ Different market verticals

Position Sizing Rules

Never Exceed:

• 10% of net worth in any single model
• 30% of net worth in Hokusai tokens total
• Amount you can't afford to lose completely

Scale positions:

High Conviction: 5-10% of crypto portfolio
Medium Conviction: 2-5% of crypto portfolio
Low Conviction: 0.5-2% of crypto portfolio
Speculative: < 0.5% of crypto portfolio

Emotional Discipline

Avoid Common Mistakes:

FOMO (Fear of Missing Out):

❌ Seeing model 5x, buying at top
✅ Stick to your research and plan

Panic Selling:

❌ Selling at -30% due to fear
✅ Follow your stop-loss strategy

Overtrading:

❌ Buying/selling daily on emotions
✅ Make deliberate, planned trades

Revenge Trading:

❌ Doubling down after losses
✅ Take breaks, reassess strategy

Advanced Strategies

How Token Holders Benefit

Current Revenue Mechanism:

• API fee deposits increase AMM reserve → token price rises
• Hold tokens and benefit from reserve growth (passive appreciation)
• Sell tokens on AMM after launch period (Day 7+)
• No active participation or staking required

What Does NOT Exist:

• No staking mechanisms
• No yield farming
• No liquidity mining
• No dividend distributions
• No governance token rewards

External Opportunities: If tokens get listed on external DEXs, you could provide liquidity there, but this would be entirely separate from the Hokusai protocol and comes with impermanent loss risk.

Arbitrage

If tokens trade on multiple venues:

Opportunity: Price discrepancy
AMM Price: $1.00
DEX Price: $1.05

Strategy:
1. Buy on AMM for $1.00
2. Sell on DEX for $1.05
3. Profit: $0.05 per token (minus fees/gas)

Risk:
- Price moves before execution
- High gas fees eat profits
- Limited opportunities

Launch Flipping

Short-term strategy for experienced traders:

Buy Days 0-1 at low prices
Sell Day 7-8 during initial hype
Target: +50-200% in 7-10 days

Risk:
- Launch fails, trapped for weeks
- Post-launch dump exceeds gains
- High stress, requires monitoring

Tax Considerations

Disclaimer: Not tax advice. Consult a tax professional.

Tax Events

Buying tokens: Not taxable (purchase) Selling tokens: Taxable capital gain/loss Receiving rewards: Taxable as income (in some jurisdictions) Transfers: Generally not taxable

Record Keeping

Essential Records:
☐ Date and time of each trade
☐ Amount of USDC spent / received
☐ Amount of tokens bought / sold
☐ Transaction hashes
☐ Fee amounts paid
☐ Purpose (investment, trade, etc.)

Tax Optimization

Hold >1 year: Long-term capital gains (lower rate in US) Tax-loss harvesting: Sell losers to offset winners Timing: Consider tax year when taking profits

Due Diligence Checklist

Before investing in any model token:

Technical Due Diligence

☐ Smart contracts are verified
☐ No major audit findings
☐ Code is open source
☐ Contract is not upgradeable (or has timelock)
☐ No admin keys or minimal permissions

Model Due Diligence

☐ Model performance data is public
☐ Benchmarks are from reputable sources
☐ Improvement trajectory is positive
☐ Use case is clear and valuable
☐ Competition is assessed

Team Due Diligence

☐ Team is doxxed or has reputation
☐ Active communication channels
☐ Responsive to community
☐ Clear roadmap and milestones
☐ No history of scams or rug pulls

Economic Due Diligence

☐ Tokenomics make sense
☐ Initial distribution is fair
☐ No excessive team allocation
☐ Fee structure is reasonable
☐ Revenue model is sustainable

Community Due Diligence

☐ Active community exists
☐ Organic engagement (not bot)
☐ Positive sentiment overall
☐ Early supporters are credible
☐ No signs of coordinated shilling

Red Flags

Avoid models with:

• ❌ Anonymous team with no track record
• ❌ Unverified or closed-source contracts
• ❌ Unrealistic performance claims
• ❌ No API usage or revenue
• ❌ Greater than 20% team token allocation
• ❌ Upgradeable contracts without timelock
• ❌ Suspicious community activity
• ❌ Copied or plagiarized code
• ❌ No documentation
• ❌ Extremely low CRR (less than 5%)

Case Studies

Successful Investment Example

Model X: NLP Translation Model

Research Phase:

• Performance: 85% accuracy, improving
• Team: Experienced AI researchers, doxxed
• Community: 500+ engaged members
• Tokenomics: 20% CRR, $25k initial reserve

Investment:

• Bought Day 1: $2,000 at $0.10/token = 20,000 tokens
• Bought Day 4: $1,000 at $0.15/token = 6,667 tokens
• Total: $3,000 for 26,667 tokens, avg $0.1125

Performance:

• Day 7: Price $0.25 (+122%)
• Day 30: Price $0.40 (+256%) due to API fees
• Day 90: Price $0.60 (+433%)

Exit:

• Sold 50% at Day 30: 13,333 × $0.40 = $5,333 (+78% on total capital)
• Holding rest: 13,333 × $0.60 = $8,000
• Total value: $13,333 (+344%)

Key Success Factors:

• Strong fundamentals
• DCA strategy reduced risk
• Partial profit-taking secured gains
• API usage drove long-term value

Failed Investment Example

Model Y: Experimental Vision Model

Research Phase:

• Performance: 70% accuracy, untested
• Team: Anonymous, new to space
• Community: Small, mostly speculators
• Tokenomics: 10% CRR, $5k initial reserve

Investment:

• Bought Day 0: $1,000 at $0.05/token = 20,000 tokens
• FOMO'd Day 2: $1,000 at $0.08/token = 12,500 tokens
• Total: $2,000 for 32,500 tokens, avg $0.0615

Performance:

• Day 7: Price $0.10 (+63%)
• Day 8: Sell pressure, price crashes to $0.04 (-35%)
• Day 30: Price $0.02 (-67%) due to no API usage

Exit:

• Sold all Day 30: 32,500 × $0.02 = $650
• Total loss: -$1,350 (-67.5%)

Key Failure Factors:

• Weak fundamentals ignored
• Anonymous team risk
• No API usage/revenue
• Low CRR = high volatility
• FOMO'd instead of following plan

Resources

Essential Links

• AMM Overview - Understand the mechanics
• Launch Period - Seven-day bonding round
• Bonding Curve Math - Formula deep dive
• HokusaiAMM Contract - Technical reference
• Buying Guide - Step-by-step buying
• Selling Guide - Step-by-step selling

Community

• Discord - Join discussions
• Forum - Long-form discussions
• Twitter - News and updates
• GitHub - Source code

Tools (Coming Soon)

• Portfolio tracker
• Model analytics dashboard
• Price alerts
• API usage metrics
• Historical performance charts

Final Thoughts

Investing in Hokusai model tokens is high risk, high reward. Success requires:

1. Thorough research - Don't invest blindly
2. Risk management - Never overallocate
3. Patience - Hold through volatility
4. Discipline - Follow your strategy
5. Continuous learning - Stay informed

Remember: Past performance doesn't guarantee future results. Always invest responsibly and never more than you can afford to lose.

Good luck, and welcome to the future of AI-backed assets!

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