Forex API
Tick-level quotes for 50+ currency pairs including majors, minors and exotics.
Stream tick-level Forex, Crypto, Stock, Commodity and Index data over a single WebSocket and REST API. Get a free key in seconds — no sales call required.
| Symbol | Asset class | Price | Latest move |
|---|---|---|---|
| EUR/USD ForexEuro / US Dollar | Forex | - | - |
| BTC/USDT CryptoBitcoin | Crypto | - | - |
| ETH/USDT CryptoEthereum | Crypto | - | - |
| AAPL StockApple Inc. | Stock | - | - |
| XAU/USD CommodityGold Spot | Commodity | - | - |
| USD/JPY ForexUS Dollar / Yen | Forex | - | - |
| NVDA StockNVIDIA Corp. | Stock | - | - |
| SPX IndexS&P 500 Index | Index | - | - |
Every market AllTick covers is available through the same unified REST and WebSocket interface.
Tick-level quotes for 50+ currency pairs including majors, minors and exotics.
Real-time spot and derivatives data, normalized into one feed.
Equities across US, Hong Kong and mainland China with trades and quotes.
Live pricing for precious metals and energy.
Benchmark index values and constituents for major global indices.
Compare coverage, latency and data types across every AllTick market.
Browse productsHow AllTick compares to a typical legacy market-data vendor.
| Capability | AllTick | Typical Legacy Vendor |
|---|---|---|
| Median WebSocket latency | ~150ms | 400–800ms |
| Asset classes in one API | 5 (FX, Crypto, Stock, Commodities, Indices) | 1–2 |
| Uptime SLA | 99.95% | 99.5% or none |
| Free tier | Yes — instant API key | Sales call required |
| WebSocket streaming | Native | Polling / limited |
Connect over WebSocket and subscribe to any symbol across any market.
# AllTick realtime financial data API
# forex crypto stock commodities indices
import asyncio, json, uuid
import websockets
subscribe = {
"cmd_id": 22004,
"seq_id": 1,
"trace": str(uuid.uuid4()),
"data": {"symbol_list": [{"code": "EURUSD"}]},
}
heartbeat = {"cmd_id": 22000, "seq_id": 1, "trace": "heartbeat", "data": {}}
async def stream():
uri = "wss://quote.alltick.co/quote-b-ws-api?token=YOUR_API_KEY"
async with websockets.connect(uri) as socket:
await socket.send(json.dumps(subscribe))
async def keep_alive():
while True:
await asyncio.sleep(10)
await socket.send(json.dumps(heartbeat))
asyncio.create_task(keep_alive())
async for message in socket:
print(json.loads(message))
asyncio.run(stream())Cut market-data costs by 60% while adding crypto coverage.
“Migrating to AllTick let us consolidate three vendors into one WebSocket feed and ship our trading app a quarter early.”Read case study
Served 40k concurrent users with sub-200ms quote updates.
“The 99.95% SLA and consistent latency were exactly what our retail brokerage needed to scale globally.”Read case study
Backtested 12 years of tick data across 5 asset classes.
“Having historical and live data from a single normalized API removed weeks of data-engineering work.”Read case study
Generate a free API key in seconds and connect to every market from one endpoint.
Generate a free API key in seconds and connect to every market from one endpoint.
Remove weeks of data-engineering work with clean, normalized historical and live data from one API and one schema.
Every asset class shares the same fields, so notebooks and pipelines generalize across markets.
Backtest and study 12+ years of tick and bar data without stitching multiple vendors together.
Deterministic timestamps and stable identifiers make results easy to reproduce and share.
| Research domain | Data granularity and depth | Example research topics |
|---|---|---|
| Market microstructure | 12+ years of raw tick data for major global Forex markets (150+ currency pairs), commodities and crypto, with L1/L2 order-book depth. | Order-flow imbalance (OFI), liquidity depletion and high-frequency limit-order-book (LOB) modelling. |
| Asset pricing and quantitative factors | Multi-interval OHLCV and volume-weighted average price (VWAP) data for major global equities, including US and Hong Kong stocks, and key derivatives indices. | Momentum effects, multi-factor models (Fama-French) and cross-asset risk-premium research. |
| Behavioural finance and volatility | Second-by-second change histories and records of sharp volume fluctuations for 1,000+ spot and perpetual-contract pairs worldwide. | Crypto-market extreme-event resonance, abrupt shifts in market sentiment and tail risk. |
| Macroeconomics and cross-market transmission | Long time series for core commodities, including gold, silver and Brent crude, and major global equity indices. | Inflation-expectation transmission and the real-time response of commodity futures to macroeconomic policy. |
In the past, empirical finance research often required weeks or months to buy, download and clean data from different exchanges and vendors. AllTick removes that barrier. Our unified cross-market schema normalizes complex international, multi-asset data into a standard format with consistent fields and UTC timestamps, so researchers can devote their full attention to econometric modelling and paper writing.
Academic research places strict demands on reproducibility. AllTick historical time series provide high-precision, millisecond deterministic timestamps and exclude bias caused by bad data, spikes or exchange transmission delays. Peers and team members using the same code and the AllTick API can reproduce identical empirical results.
Whether you analyse data in Jupyter Notebook with Pandas and NumPy, build complex GARCH volatility models in R, or use MATLAB for matrix computation, AllTick standard REST API lets you retrieve large datasets asynchronously in only a few lines of code.
We understand the needs of academic research and laboratory budgets. AllTick offers cost-effective academic sponsorship programmes for university professors, doctoral students and financial laboratories, with flexible licences that support sharing cleaned research samples within teams and research groups to speed paper publication.
Scenario: retrieve historical K-line data in one call for time-series regression analysis (Python example).
import pandas as pd
import requests
def load_research_dataset(symbol, start_date, end_date):
"""
Load AllTick historical financial time-series data into an academic-standard Pandas DataFrame.
"""
api_key = "YOUR_RESEARCH_API_KEY"
url = f"https://alltick.co"
params = {
"symbol": symbol,
"resolution": "60", # 1-hour (1H) K-line, ideal for intraday econometric analysis
"start_time": start_date,
"end_time": end_date,
"key": api_key
}
response = requests.get(url, params=params)
data = response.json()
# Extract K-line data and convert it to a DataFrame
df = pd.DataFrame(data['candles'])
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s')
df.set_index('timestamp', inplace=True)
return df
if __name__ == "__main__":
print("Retrieving BTCUSD and gold (XAUUSD) historical cross-market research samples...")
# Load clean, research-grade time series automatically
df_crypto = load_research_dataset("BTCUSD", "1740000000", "1740500000")
# The data is fully aligned: call .describe(), .plot() or run multivariate regression directly
print(df_crypto.head())Generate a free API key in seconds and connect to every market from one endpoint.