The data covers tick, minute (1m), and hourly (1h) resolutions, allowing for sophisticated intraday analysis and backtesting.
Example of utilizing minute-resolution stock prices for analyzing financial news events. Common Use Cases
Analyzing how spreads change or studying liquidity patterns.
Data spans decades across major and exotic Forex pairs, commodities (Gold, Silver, Oil), stock indices, and cryptocurrencies. dukascopy+historical+data
In the world of algorithmic and retail trading, the phrase "garbage in, garbage out" is the ultimate commandment. The quality of your backtest is only as good as the data you feed into your strategy. For serious traders—whether you are a quantitative hedge fund manager or a dedicated retail Forex scalper—one name consistently rises to the top when discussing tick-by-tick accuracy: .
Because the SWFX marketplace pools liquidity from over 20 major banks, the data reflects actual institutional market depth rather than a single retail broker's skewed feed. Data Structure and Formats
Among retail traders and institutional developers alike, is widely considered the gold standard for free, high-quality Forex historical data. This article explores why Dukascopy historical data is highly valued, its structure, and how to download and utilize it for your trading systems. Why Choose Dukascopy Historical Data? The data covers tick, minute (1m), and hourly
Unlike brokers that only offer 1-minute (M1) bars, Dukascopy provides actual tick data containing individual price changes with millisecond timestamps.
When working with Dukascopy historical data, keep the following tips and best practices in mind:
For algorithmic traders, the reliability of data is non-negotiable. Backtesting on flawed data leads to "curve fitting" and live losses. Data spans decades across major and exotic Forex
| Library | Language | Key Features | | :--- | :--- | :--- | | dukascopy-python | Python | DataFrames via fetch() and live streaming via live_fetch() ; returns pandas.DataFrame for easy analysis. | | dukascopy-node | Node.js / CLI | CLI usage -i btcusd -from 2019-01-13 -to 2019-01-14 -t tick -f csv ; programmatic functions getHistoricalRates() . | | dukascopy (Elixir) | Elixir / CLI | Command-line tool to search instruments and download data with various formatting options (CSV, JSON). Supports over 1600 instruments. | | tradedesk-dukascopy | Python | Auto-decompresses .bi5 tick files; can be resampled to OHLCV candles; exports clean CSV files. | | paracas-lib | Rust | High-performance and concurrent downloads; outputs to CSV, JSON, and Parquet formats for speed. |
All Dukascopy data is strictly recorded in Coordinated Universal Time (UTC). If your trading strategy relies on specific session times (like the New York open), you must shift the timestamps in your code or testing platform to account for your target timezone.
Dukascopy stores its data publicly on its servers, but it is not saved in a standard CSV format. To download it directly, you must understand how it is structured. File Format and Compression
Dukascopy historical data represents a democratization of financial market information. By providing free, high-quality tick data, Dukascopy empowers retail traders and small hedge funds to compete with larger institutions on the basis of rigorous quantitative analysis.
