Dukascopy Historical Data Exclusive [hot] Link
Most free data sources provide "smoothed" data or simple mid-prices. Dukascopy archives every single price change for both the and Ask lines, down to the millisecond, accompanied by real executed volume. This allows you to simulate true spread widening, slippage, and liquidity gaps. 3. Deep Asset Coverage
Unlike many retail brokers whose data feeds are filtered through market-maker models, the SWFX feed combines liquidity from over 50 major financial institutions, including banks, hedge funds, and other large liquidity providers. This aggregation process generates a dense, raw data stream that captures every market nuance, which is then made available to traders at no cost—an industry rarity for ECN-level granularity.
Decompress the hourly .bi5 binary files using the LZMA algorithm.
A vast array of community-driven tools has been built to interact with Dukascopy's data, including , dukascopy-node (Node.js) , and a Rust library for high-performance parsing of bi5 files. dukascopy historical data exclusive
Floating-point or integer representation of liquidity available at the Bid. Methods to Download and Export the Data
Here is a conceptual layout of how a Python script handles the binary parsing:
When you download Dukascopy historical data, you aren't just getting a timestamp; you are getting a transaction record. This allows for advanced strategies that time-based data cannot support, such as: Most free data sources provide "smoothed" data or
Sourced from a regulated Swiss bank with a massive liquidity pool of 20+ banks. Deep History:
October 26, 2023 Subject: Analysis of Dukascopy Historical Data Availability, Access Methods, and Competitive Advantage
Backtest across Major and Exotic Forex pairs, Commodities, Indices, Cryptocurrencies, and Stocks. Decompress the hourly
Access over 15 years of high-quality history for 60+ Forex pairs and 1,600+ instruments, including metals, indices, and crypto. Gap-Free Reliability:
Dukascopy does not provide a simple "Download CSV" button for the entire dataset. Access is segregated by the intended use case:
Raw historical data is often riddled with errors: outliers, time-zone misalignments, and gaps in reporting. Part of the "exclusivity" of working with premium historical datasets is the preprocessing work required.
Historical data is stored as four base periods (Ticks, 1 Minute, 1 Hour, 1 Day). All other timeframes (e.g., 5-minute or Renko charts) are calculated directly from these base sources to maintain total consistency. For Research Purposes