TickAtlas

Use Case

Market Making

Real-time spread data, tick-level quotes, volatility indicators, and high-frequency-ready response times for building competitive market-making algorithms.

The Challenge

Market makers profit from the bid-ask spread while managing inventory risk. This requires continuous monitoring of current spreads, tick-level price movements, and volatility conditions that affect optimal quote width. You need a data source that delivers real-time quotes and spread analytics without the overhead of maintaining direct exchange connections, plus volatility indicators to dynamically adjust your quoting strategy.

How TickAtlas Solves It

Real-Time Spread Data

/v1/spread returns current spread, average spread, and spread percentile. Know exactly where the market is quoting.

Tick Data Stream

/v1/ticks provides raw bid/ask tick data with timestamps. Track every price movement for quote adjustment.

Volatility Indicators

ATR, Bollinger Band width, and StdDev on short timeframes. Widen quotes during high volatility, tighten during calm.

Sub-100ms Latency

Redis-cached responses with 2-second TTL. Enterprise plan: 6,000 req/min for continuous high-frequency polling.

Multi-Symbol Quotes

/v1/multi fetches quotes and indicators for your entire book in a single request. Reduce round-trips.

Session Awareness

/v1/sessions tells you which markets are open. Adjust quoting behavior for London, New York, and Asian sessions.

Key Endpoints

GET /v1/spread?symbol=EURUSD

Current spread, average, min, max, and percentile
GET /v1/ticks?symbol=EURUSD&limit=500

Raw bid/ask ticks for micro-structure analysis
GET /v1/indicator?name=atr&timeframe=M5

Short-term ATR for dynamic quote width adjustment
GET /v1/sessions

Market session status for liquidity-aware quoting

Market Making Architecture

architecture 
┌──────────────────────────────────────────────────────────────┐
│                  Market Making Engine                         │
│                                                              │
│  ┌──────────────┐  ┌───────────────┐  ┌──────────────────┐   │
│  │ Tick Monitor  │  │ Spread        │  │ Volatility       │   │
│  │ /v1/ticks     │  │ /v1/spread    │  │ /v1/indicator     │   │
│  │ (100ms poll)  │  │ (1s poll)     │  │ ATR, BB Width    │   │
│  └──────┬───────┘  └──────┬────────┘  └──────┬───────────┘   │
│         │                 │                   │               │
│         └─────────┬───────┴──────┬────────────┘               │
│                   ▼              ▼                             │
│           ┌──────────────────────────┐                        │
│           │ Quote Calculator          │                        │
│           │ mid_price +/- f(ATR, vol) │                        │
│           └──────────┬───────────────┘                        │
│                      ▼                                        │
│           Submit bid/ask to venue                              │
└──────────────────────────────────────────────────────────────┘

Code Example

python 
import requests

API_KEY = "your_api_key"
BASE = "https://tickatlas.com/v1"
headers = {"X-API-Key": API_KEY}

def calculate_quote_width(symbol):
    """Dynamic quote width based on current volatility and spread."""

    # Current spread conditions
    spread = requests.get(f"{BASE}/spread",
        headers=headers, params={"symbol": symbol}).json()
    current_spread = spread["data"]["current_spread_pips"]
    avg_spread = spread["data"]["average_spread_pips"]

    # Short-term volatility (ATR on M5)
    atr = requests.get(f"{BASE}/indicator", headers=headers,
        params={"symbol": symbol, "name": "atr", "timeframe": "M5"}).json()
    atr_value = atr["data"]["value"]

    # Bollinger Band width for volatility regime
    bb = requests.get(f"{BASE}/indicator", headers=headers,
        params={"symbol": symbol, "name": "bollinger-bands", "timeframe": "M5"}).json()
    bb_width = bb["data"]["width"]

    # Dynamic quote width: wider in volatile markets
    base_width = max(current_spread * 1.2, avg_spread)
    vol_multiplier = 1.0 + (bb_width / 0.01)  # Wider BB = wider quotes
    quote_width = base_width * vol_multiplier

    return {
        "symbol": symbol,
        "bid_offset": -quote_width / 2,
        "ask_offset": +quote_width / 2,
        "atr": atr_value,
        "bb_width": bb_width,
        "spread": current_spread
    }

# Calculate for your book
for sym in ["EURUSD", "GBPUSD", "USDJPY"]:
    quote = calculate_quote_width(sym)
    print(f"{sym}: width={quote['ask_offset'] - quote['bid_offset']:.1f} pips "
          f"(ATR={quote['atr']:.5f}, spread={quote['spread']:.1f})")

Recommended Plan

Enterprise Plan

$349/mo

Market making requires the highest request volumes and lowest latency. Enterprise gives 1,000,000 requests/day, 6,000 req/min, and SLA guarantees for production systems.

  • ✓ 6,000 req/min for continuous high-frequency polling
  • ✓ /v1/ticks and /v1/spread for micro-structure data
  • ✓ SLA guarantee and dedicated support
  • ✓ 100 API keys for distributed systems
View all plans →

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