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.

Most people look at the market through a compressed lens—candlesticks, indicators, moving averages, and other aggregated views. They are useful, but they already abstract away the real trading process. The actual market doesn’t operate in n
Most people look at the market through a compressed lens—candlesticks, indicators, moving averages, and other aggregated views. They are useful, but they already abstract away the real trading process. The actual market doesn’t operate in neat time buckets. It moves tick by tick, where each update represents a single micro event rather than a summary of behavior.
In tick data, every update usually contains three core fields: price, volume, and timestamp. On the surface, they look simple. But together, they form the smallest meaningful representation of market microstructure. Price tells you where the update happened, volume tells you the strength behind it, and timestamp places it precisely in time. Individually they seem basic, but combined, they reveal the real rhythm of the market.
People are used to seeing the market as a visual object—charts with clean lines and patterns. But in reality, it behaves more like a continuous stream of events. Each tick represents an interaction between buyers and sellers, either through aggressive execution or passive quote updates. These interactions are not evenly distributed. They come in bursts, pauses, clusters, and sometimes long periods of inactivity.
This uneven structure is not noise—it is the market itself. What appears as smooth trends on candlestick charts is actually the result of many irregular micro-level movements compressed into a single visual form. At tick level, those movements become visible again, and the structure looks very different.
Price is the most obvious element in each tick. It shows the latest level at which the market has updated or traded. However, price alone does not explain why the market moved.
A rising sequence of prices does not necessarily mean strong buying pressure. It can also be caused by thin liquidity or temporary imbalance, where small orders move the price more easily than usual. This is especially common during news events or low-liquidity periods, where price becomes more volatile and less structurally meaningful.
In this sense, price reflects the outcome of market activity, not the intention behind it.
Compared to price, volume provides deeper context. It shows whether a price movement is supported by meaningful participation or just drifting on weak activity.
When rising prices are accompanied by strong volume, it usually indicates genuine market participation. But when price moves with low volume, the move becomes structurally fragile and more likely to reverse. Another important case is high volume with little price movement, which often indicates absorption—large participants taking opposite sides without allowing significant price change.
Volume, therefore, helps reveal intent behind price action rather than just direction.
Timestamp is often ignored because it does not directly affect direction or magnitude, but it defines the structure of how market activity unfolds over time.
Ticks that arrive in rapid bursts usually indicate heightened activity, often driven by news events, algorithmic reactions, or sudden liquidity shifts. In contrast, slower tick arrival suggests reduced participation and more cautious market behavior.
What makes timestamp particularly important is that it reveals differences that are invisible on aggregated charts. Two price movements that look identical on a candlestick chart may have completely different internal structures when analyzed at tick level—one driven by steady flow, another by sharp bursts of activity compressed into a short time window.
When price, volume, and timestamp are analyzed together, the market starts to resemble a behavioral system rather than a simple time series. You begin to observe short-lived momentum bursts, liquidity gaps appearing and disappearing, and micro-patterns that never show up on higher timeframe charts.
This is the essence of market microstructure: not predicting long-term direction, but understanding how market behavior unfolds at the smallest observable scale. It is more about interaction than prediction, more about structure than outcome.
In real systems, tick data is usually handled through a pipeline. Data is first ingested in real time, then cleaned and time-aligned. After that, it is grouped into very small time windows such as 100ms or 1-second intervals. From these windows, features are extracted, including short-term price changes, volume intensity, and tick frequency.
These features can then be used for trading strategies, monitoring systems, or risk models. However, the main challenge is not the logic itself, but data consistency. Tick streams can arrive out of order, experience delays, or become noisy during high volatility, which can distort downstream analysis if not handled properly.
At a deeper level, the quality of analysis depends heavily on the quality of input data. If price, volume, or timestamp is inconsistent or misaligned, even slightly, the entire interpretation becomes unreliable.
This is why many developers rely on dedicated infrastructure rather than building everything from scratch. For example, the AllTick API provides structured tick-level data across multiple markets, reducing the need for heavy preprocessing and allowing developers to focus more on analysis and modeling rather than data cleanup.
A single tick on its own carries very little meaning. But when you observe ticks in sequence, the market starts to reveal its internal structure. Price shows movement, volume shows participation, and timestamp shows how that participation unfolds over time.
Together, they form the foundation of market microstructure. And once you start seeing the market at this level, aggregated views like candlesticks often feel like a simplified summary that misses most of the real behavior underneath.
Generate a free API key in seconds and connect to every market from one endpoint.