┌─────────────────────────────────────────────────────────────────────┐
│                    QUOTING REQUIREMENTS BY TIER                      │
├─────────────────────────────────────────────────────────────────────┤
│                                                                      │
│  Metric          │ Tier 1  │ Tier 2  │ Tier 3  │ Tier 4            │
│  ─────────────────┼─────────┼─────────┼─────────┼─────────          │
│  Max Spread       │ 10 bps  │ 5 bps   │ 3 bps   │ 2 bps            │
│  Min Depth/Side   │ $50K    │ $250K   │ $1M     │ $5M              │
│  Uptime           │ 85%     │ 90%     │ 92%     │ 95%              │
│  Depth Levels     │ 1       │ 3       │ 5       │ 10               │
│  RFQ Response     │ 500ms   │ 200ms   │ 50ms    │ 10ms             │
│  Quote Update     │ 1s      │ 500ms   │ 100ms   │ 10ms             │
│                                                                      │
└─────────────────────────────────────────────────────────────────────┘

# Spread calculated as percentage of mid-price
spread_bps = ((best_ask - best_bid) / mid_price) * 10000

# Example: BTC-USD
best_bid = 50000.00
best_ask = 50005.00
mid_price = (best_bid + best_ask) / 2  # 50002.50
spread_bps = ((50005 - 50000) / 50002.50) * 10000  # 1.0 bps

Spread Compliance Score = (Compliant Samples / Total Samples) * 100

Sampling:
- Frequency: Every 100ms during trading hours
- Window: 24/7 for crypto markets
- Exclusions: Scheduled maintenance, force majeure events

Compliance Thresholds:
- Tier 1: 85% of samples within max spread
- Tier 2: 90% of samples within max spread
- Tier 3: 92% of samples within max spread
- Tier 4: 95% of samples within max spread

Tier 2+ Depth Level Requirements:

Level 1: Best bid/ask (within max spread)
Level 2: +0.1% from Level 1
Level 3: +0.2% from Level 1
Level 4: +0.3% from Level 1 (Tier 3+)
Level 5: +0.5% from Level 1 (Tier 3+)
Level 6-10: +1.0% increments (Tier 4 only)

// Example: BTC-USD depth for Tier 3 MM
const midPrice = 50000;
const requirements = {
  level1: { price: midPrice * 1.0003, minSize: 5.0 },   // $250K
  level2: { price: midPrice * 1.0010, minSize: 2.5 },   // $125K
  level3: { price: midPrice * 1.0020, minSize: 2.5 },   // $125K
  level4: { price: midPrice * 1.0030, minSize: 2.5 },   // $125K
  level5: { price: midPrice * 1.0050, minSize: 7.5 },   // $375K
  // Total: $1M per side
};

Uptime % = (Time with Valid Quotes / Total Scheduled Time) * 100

Valid Quote Definition:
- Both bid and ask prices present
- Spread within maximum allowed
- Depth meets minimum requirements
- Prices updated within freshness window

Unplanned Downtime Protocol:

1. Detection
   - System detects missing/stale quotes
   - 30-second grace period before flagging

2. Notification
   - Alert sent to MM operations team
   - Status page updated

3. Escalation (after 5 minutes)
   - Dedicated support contacted
   - Incident ticket created

4. Resolution
   - MM must provide incident report within 24 hours
   - Repeated incidents may affect tier status

# Quote freshness monitoring
def is_quote_fresh(quote, tier):
    max_age_ms = {1: 1000, 2: 500, 3: 100, 4: 10}
    quote_age = time.now() - quote.timestamp
    return quote_age < max_age_ms[tier]

# Stale quotes are:
# - Not counted toward uptime
# - Not eligible for maker rebates
# - Flagged in performance reports

// RFQ Request
{
  "type": "rfq_request",
  "request_id": "rfq_12345",
  "symbol": "BTC-USD",
  "side": "buy",
  "size": "10.0",
  "timestamp": 1702300800000
}

// RFQ Response
{
  "type": "rfq_response",
  "request_id": "rfq_12345",
  "bid": "50000.00",
  "ask": "50002.00",
  "bid_size": "15.0",
  "ask_size": "15.0",
  "valid_until": 1702300805000,
  "timestamp": 1702300800005
}

┌─────────────────────────────────────────────────────────────────┐
│  MARKET MAKER PERFORMANCE DASHBOARD                              │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  Current Status: ● COMPLIANT                                    │
│                                                                  │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐             │
│  │ Uptime      │  │ Avg Spread  │  │ Total Depth │             │
│  │   94.3%     │  │   2.1 bps   │  │   $12.5M    │             │
│  │ Target: 92% │  │ Max: 3 bps  │  │ Min: $10M   │             │
│  └─────────────┘  └─────────────┘  └─────────────┘             │
│                                                                  │
│  Markets Quoted: 35/30 required                                 │
│  RFQ Response: 45ms avg (Target: <50ms)                        │
│  Quote Updates: 85ms avg (Target: <100ms)                      │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘

# Recommended quote update strategy
class QuoteManager:
    def update_quotes(self, market_data):
        # 1. Calculate fair value
        fair_value = self.calculate_fair_value(market_data)

        # 2. Determine spread based on volatility
        spread = self.calculate_spread(market_data.volatility)

        # 3. Set depth based on inventory
        depth = self.calculate_depth(self.inventory)

        # 4. Apply risk limits
        quotes = self.apply_risk_limits(fair_value, spread, depth)

        # 5. Send atomic update
        self.send_quotes(quotes)