Backtest on real ticks
Access years of tick-level history with consistent timestamps so your backtests match live execution conditions.
Solutions
Quantitative Traders
Build, backtest and run systematic strategies on gap-checked tick data and a single normalized real-time feed across every asset class.
Clean tick history and low-latency streaming for systematic strategies.
One feed, five markets
Trade FX, crypto, equities, commodities and indices through the same schema, with no per-vendor adapters.
Sub-150ms streaming
Native WebSocket delivery keeps signal-to-order latency tight for intraday and higher-frequency models.
Core technical specs and coverage
One normalized feed for the instruments and history systematic traders need to research, test and operate.
| Asset class | Coverage | History depth | Delivery |
|---|---|---|---|
| Forex | 150+ currency pairs, including G10, emerging-market currencies and precious-metal crosses | 10+ years of tick-level historical data | REST / WebSocket streaming |
| Crypto | 1,000+ spot and perpetual pairs aggregated across leading global exchanges | 5+ years of complete order book history | Millisecond incremental updates |
| Stocks | US stocks across NYSE and NASDAQ, Hong Kong stocks and other major equities and ETFs | Time & Sales plus L1/L2 data | Continuous real-time feed with pre-market and after-hours coverage |
| Commodities and indices | Brent crude, gold, silver, S&P 500, Nasdaq 100 and other major global instruments | High-frequency history for core index constituents | Normalized fields across markets |
End-to-end quant workflow
Move from clean research data to production execution and live risk controls through one market-data connection.
Alpha generation and factor research
Use rigorously cleaned, gap-checked tick data to build more precise high-frequency factors for momentum, market microstructure and order-flow resistance while reducing noise-driven survivorship bias.
High-fidelity backtesting
Historical tick data uses globally consistent UTC timestamps. Connect Python (Pandas/NumPy), C++, Go and other major frameworks so your matching engine can reproduce slippage and market impact costs.
Live execution and order routing
Sub-150ms WebSocket streaming is designed for intraday statistical arbitrage, market making and CTA strategies, helping you route orders when signals fire and capture small spread opportunities.
Real-time risk management
Monitor depth and volatility across asset classes through one connection. Calculate VaR and margin requirements dynamically to reduce liquidation risk during events such as non-farm payrolls or crypto shocks.
Developer SDKs and code snippets
Start with a practical WebSocket subscription or a REST history request, then adapt the same normalized schema to your research stack.
# AllTick — Real-time Financial Market Data API
# Real-time Forex, Stocks, Crypto, Commodities and Indices market data
import json
import os
import threading
import time
import uuid
import websocket
# Subscribe to gold and Bitcoin on the general-market gateway.
def on_open(ws):
ws.send(json.dumps({
"cmd_id": 22004,
"seq_id": 1,
"trace": str(uuid.uuid4()),
"data": {"symbol_list": [{"code": "XAUUSD"}, {"code": "BTCUSDT"}]},
}))
def keep_alive():
while ws.sock and ws.sock.connected:
time.sleep(10)
ws.send(json.dumps({"cmd_id": 22000, "seq_id": 2, "trace": "heartbeat", "data": {}}))
threading.Thread(target=keep_alive, daemon=True).start()
def on_message(_ws, message):
print(json.loads(message))
if __name__ == "__main__":
token = os.environ["ALLTICK_API_TOKEN"]
socket = websocket.WebSocketApp(
f"wss://quote.alltick.co/quote-b-ws-api?token={token}",
on_open=on_open,
on_message=on_message,
)
socket.run_forever()Start streaming market data today
Generate a free API key in seconds and connect to every market from one endpoint.
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