🎯 Try it now → https://naklitechie.github.io/PredictionMarket/

A browser-native educational simulator demonstrating how prediction markets work. Control 4 simulated players to explore two market mechanisms: Parimutuel and LMSR (Logarithmic Market Scoring Rule).

• All players place bets into a shared pool
• Winning bets split the entire pool proportionally
• Payout formula: stake × (total_pool / total_on_winning_side)
• Simple one-off betting market

• Continuous market with dynamic prices
• Each trade immediately affects the odds
• Cost function: C(q) = b × ln(exp(q_yes/b) + exp(q_no/b))
• Price formula: p_yes = exp(q_yes/b) / (exp(q_yes/b) + exp(q_no/b))
• Configurable liquidity parameter b

• 4 simulated players (A, B, C, D) controlled by one operator
• Binary yes/no markets with optional labeled outcomes
• Real-time updates of odds, prices, and balances
• Clear resolution and payout calculation
• Trade/bet history tracking

# Clone or download this repo
# Option 1: Python
python3 -m http.server 8000

# Option 2: Node.js
npx serve .

# Option 3: Just open index.html directly in your browser

Then visit http://localhost:8000

Works on any static host:

• GitHub Pages
• Netlify
• Vercel
• python3 -m http.server

No build step, no dependencies, no API keys.

• Total Pool: $450
• YES Total: $300, NO Total: $150
• If YES wins: YES bettors split $450 → each $1 gets $1.50 back
  • Player A: $100 × 1.5 = $150 returned (+$50 profit)
  • Player B: $200 × 1.5 = $300 returned (+$100 profit)
  • Player C: $0 returned (-$150 loss)

Starting state: q_yes = 0, q_no = 0, b = 100

1. Player A buys 10 YES shares

   • Cost: ~$5.12 (calculated via LMSR cost function)
   • New state: q_yes = 10, q_no = 0
   • New P(YES): ~0.525

2. Player B buys 20 NO shares

   • Cost: ~$10.95
   • New state: q_yes = 10, q_no = 20
   • New P(YES): ~0.422

3. Resolution: If YES wins, each YES share redeems for $1

   • Player A: 10 shares × $1 = $10 (bought for $5.12 → +$4.88 profit)
   • Player B: 0 shares redeem (bought NO shares) → -$10.95 loss

Edit these values in the code or UI:

// Number of players (hardcoded to 4 in v1)
// To change: modify lmsrState.players object

// Initial cash per player (LMSR mode)
initialCash: 1000  // Line ~600

// LMSR liquidity parameter
b: 100  // Lower = more volatile prices, Higher = more stable

// Default stake/share amounts
// Adjust in the HTML input defaults

Coloured with bauhaus-10 · 1933 CLOSED — the closing of the Dessau Bauhaus on 11 April 1933 and the diaspora that followed (Chicago, Tel Aviv, Harvard, Black Mountain). Pure black, signal-yellow ink, primary-red NO vs primary-blue YES. Manifesto severity, fitting for a market where every position is a declaration.

Palette pulled from Rangrez, the global colour-palette library that backs all NakliTechie projects.

browser-prediction/
├── index.html      # Single-file app (markup + styles + logic)
├── README.md       # This file
├── ideas.md        # Series vision document
└── LICENSE

• Economics classes: Demonstrate market mechanics without real money
• Workshops: Show how prediction markets aggregate information
• Product demos: Explain Polymetier, Augur, or similar platforms
• Personal learning: Experiment with different trading strategies

• ❌ No real money or wallets
• ❌ No authentication or multi-user networking
• ❌ No advanced order types (limit orders, shorts)
• ❌ No fees or regulatory compliance
• ❌ Not production-ready for real betting

This is purely an educational simulator.

MIT — See LICENSE file.

Built by Chirag Patnaik