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.
Practical writing on market data engineering, streaming APIs and building low-latency financial applications.
Generate a free API key in seconds and connect to every market from one endpoint.

When building a forex quantitative trading system, many developers initially focus on strategy models, indicator design, and execution speed. However, the factors that truly affect the reliability of analysis results often come from more fu
When building a forex quantitative trading system, many developers initially focus on strategy models, indicator design, and execution speed. However, the factors that truly affect the reliability of analysis results often come from more fundamental data processing stages.
The forex market operates as a global decentralized market, where currency pairs such as EUR/USD, GBP/USD, and USD/JPY continuously generate quote changes. For systems that rely on short-term analysis, high-frequency trading, or market microstructure research, a single missing tick data point or an incorrect time sequence can cause the strategy to misinterpret market conditions.
The core of tick data analysis is not simply obtaining prices, but ensuring that every piece of data accurately represents the actual process of market events. Only after missing data and timestamp issues are properly addressed can subsequent backtesting, model training, and live trading provide meaningful references.
Compared with stock markets, the forex market does not have a single centralized exchange. Market prices are usually formed through multiple liquidity providers. Due to differences in data sources, network transmission, and system processing speeds, market data received within the same period may experience ordering changes.
For example:
EURUSD 1.08521 10:30:01.102
EURUSD 1.08522 10:30:01.108
EURUSD 1.08520 10:30:01.105
If the system saves data according to the receiving order, it would assume that the price first increased and then declined. However, the actual market time of the third tick is earlier than the second one. It only arrived later because of network latency.
This situation becomes more noticeable during periods of high market volatility, increased data traffic, or after reconnecting a data stream. Therefore, when processing forex tick data, the first step is not calculating indicators, but ensuring that the data sequence matches the actual market timeline.
In forex market analysis, timestamps are often overlooked but represent one of the most critical data fields.
Many systems directly use local receiving time, but in reality, market data may contain different types of timestamps:
These timestamps are not always exactly the same. For example, a EUR/USD quote may already have been generated in the market, but due to network latency, it may only reach the trading system several hundred milliseconds later. If a strategy uses receiving time for analysis, communication delay may be incorrectly interpreted as market movement.
For normal market display applications, this difference may have limited impact. However, for short-term strategies, market-making systems, or high-frequency models, millisecond-level differences can affect:
Therefore, when performing forex data cleaning, it is necessary to unify the time standard and clearly define the source of each timestamp field.
Many people believe that losing a small amount of tick data will not affect the overall market trend. However, in quantitative trading scenarios, the impact is often more significant than expected.
For example, a complete price movement:
10:00:00.001 EURUSD 1.08210
10:00:00.005 EURUSD 1.08211
10:00:00.008 EURUSD 1.08212
If the middle data point is missing:
10:00:00.001 EURUSD 1.08210
10:00:00.008 EURUSD 1.08212
The system will interpret this as a rapid price jump, while the actual market may have experienced only a series of small incremental movements.
This difference may affect:
Especially during news events or periods of rapidly changing liquidity, missing tick data may make market behavior appear more extreme than it actually was. Therefore, tick data processing should not only focus on whether prices exist, but also whether the data stream remains continuous.
In real market data systems, tick data usually does not directly enter strategy models. Instead, it needs to go through cleaning and standardization processes.
The first step is field normalization.
Different market data sources may return different formats, so the following elements need to be standardized:
For example:
{
"symbol": "EURUSD",
"price": 1.08521,
"timestamp": 1786348800125
}
After entering the system, all data needs to be stored according to unified rules.
The second step is timestamp validation.
By calculating the time interval between adjacent ticks, systems can determine whether abnormal gaps exist:
gap = current_timestamp - previous_timestamp
if gap > threshold:
print("Possible missing tick")
If the tick interval suddenly increases from several milliseconds to several seconds, further analysis is needed to determine whether this is caused by naturally reduced market activity or a data transmission issue.
In addition, duplicate records, backward timestamps, and abnormal price data should also be filtered to prevent incorrect information from affecting subsequent analysis.
For developers who need to build quantitative trading systems, market analysis platforms, or financial applications, a stable data source is the foundation of the entire system.
AllTick API provides forex real-time market data and historical market data interfaces, supporting access to data for multiple global currency pairs. It also provides tick-level market data capabilities, helping developers reduce the cost of integrating multiple data sources and performing initial data cleaning.
Through real-time market data streams, developers can apply tick data to:
AllTick’s forex data API supports both real-time market data and historical data access. It is designed for quantitative investment and trading platform scenarios, allowing developers to quickly integrate market data systems.
A simple data receiving logic example:
def on_message(ws, message):
data = json.loads(message)
symbol = data["symbol"]
price = data["price"]
timestamp = data["timestamp"]
print(
symbol,
price,
timestamp
)
In a real production environment, additional mechanisms such as automatic reconnection, local caching, timestamp validation, and abnormal recovery processes are required to ensure long-term stable market data operation.
Forex tick data is not simply a collection of price records. It represents the continuous process of market activity.
Price reflects market changes, timestamps determine event order, and continuous data flow represents the actual rhythm of trading activity. If problems occur in these areas, even a well-designed strategy may produce distorted results due to inaccurate input data.
For quantitative systems, improving analytical capability is not only about obtaining more data, but also about ensuring that every tick accurately describes the market.
After forex tick data has been properly cleaned, sorted, and validated, developers can truly utilize microstructure market information to build more stable and reliable trading systems.
Generate a free API key in seconds and connect to every market from one endpoint.