Dukascopy Historical Data !!exclusive!! Jun 2026

: Some historical gaps exist. For example, user reports have highlighted missing tick data for some periods (like a 23-minute gap in EURUSD tick data in September 2011) even though bar data for the same period appears complete. Another example includes a missing 5-day window in June 2009 for JPY-related pairs (USDJPY, EURJPY, GBPJPY) and USDCHF. It is not guaranteed that historical bar data will always be consistent with the raw tick data, as they can be sourced from different collection or reconstruction processes.

For those looking to explore this data, it's highly recommended to utilize a reliable, consistent source for reliable backtesting and analysis.

Time (GMT), Open, High, Low, Close, Volume 2023-01-02 00:00:00, 1.0698, 1.0705, 1.0692, 1.0701, 1234 2023-01-02 00:01:00, 1.0701, 1.0710, 1.0698, 1.0708, 987

For tick data, each row represents a single bid/ask tick or trade. dukascopy historical data

The URL path uses a zero-indexed month (e.g., January is 00 , December is 11 ).

Many people use MetaTrader 4 (MT4) or MetaTrader 5 (MT5) to access historical forex data. To access historical data on MT4 or MT5, Dukascopy Bank SA Forex Historical Data Feed :: Dukascopy Bank SA

These contain the actual tick simulation data and go into the tester/history folder. Step 4: Run the Backtest : Some historical gaps exist

Dukascopy stores data in binary format .bi5 files. The files are organized by the hour: [Year]/[Month]/[Day]/[Hour]h_ticks.bi5

For developers and quantitative researchers, Dukascopy provides programmatic access through its formal APIs.

The JForex platform includes the , which enables users to access historical bars, ticks, order history, and feed history. This interface provides methods like getBars() and getTicks() for programmatically accessing data within the JForex environment. A key advantage is the ability to download more custom timeframes, such as price-based Renko charts, directly from the JForex trading system. It is not guaranteed that historical bar data

Download EURUSD data for a specific date range:

While Dukascopy's data is excellent, it is not without its nuances and potential pitfalls.

For developers and algorithmic traders using Python, R, or C++, open-source scrapers are readily available on GitHub (e.g., nhedger/dukascopy-node or Python-based scrapers). These tools allow you to pipe raw data directly into automated data pipelines or local databases like PostgreSQL or InfluxDB. Step-by-Step Pipeline: From Raw Data to MT4/MT5 Backtest