Dukascopy+historical+data [VALIDATED]
What do you plan to use? (e.g., Python, MT4, MT5, NinjaTrader) Which currency pairs or assets do you need data for?
Every tick includes both the bid and ask price, allowing you to accurately simulate spreads, slippage, and transaction costs.
Another widely used tool that automates the downloading process and helps launch MT4 with custom tick data to bypass MetaTrader's native history limitations. Processing and Formatting the Data
Map these files to your MT4 installation's history and tester folders. dukascopy+historical+data
The data is commonly downloaded as a .csv file, which is easy to import into tools like MATLAB, Python, or MT4/MT5. Applications of Dukascopy Data in Quantitative Finance
Unlike many offshore brokers, Dukascopy operates under stringent Swiss banking regulations. This institutional oversight ensures that the data isn't "smoothed" or manipulated.
Retrieve major currency pairs dating back to 2003, allowing you to backtest strategies across multiple market cycles and economic crises. What do you plan to use
The Ultimate Guide to Dukascopy Historical Data: Empowering Traders and Researchers
| | Dukascopy | Commercial Alternatives (e.g., Bloomberg, Dukascopy) | | :--- | :--- | :--- | | Cost | Free (for the feed) | High subscription fees | | Depth | Best Bid/Ask only (No Level 2) | Level 2 (Market Depth) often available | | Data Revision | May change historically as ticks are added | Typically fixed snapshots | | Convenience | Requires API or scripting for bulk | Immediate platform integration |
You have the data. Now, what can you do that 99% of traders cannot? Another widely used tool that automates the downloading
The detailed nature of tick data is ideal for training machine learning models. Researchers often use this data for time-series forecasting, volatility analysis, and applying ML techniques to financial data. Technical Analysis Validation
| Tool | Primary Language | Key Feature | Best For | | :--- | :--- | :--- | :--- | | | Python / CLI | Consolidates daily files into a single CSV/Parquet file | Users needing a simple, fast CLI tool for bulk downloads. | | tick-vault | Python | Concurrent downloads with resume capability and gap detection | Quantitative researchers building robust data pipelines. | | dukascopy-python | Python | Fetches static history or streams live updates as DataFrames | Python users who want quick access to data in a pandas DataFrame. | | dukascopy-node | Node.js / CLI | Direct, programmable access to data for 800+ instruments | JavaScript/TypeScript developers or users comfortable with npm. | | Dukascopy (Hex) | Elixir | Fetches historical and streaming data for 1600+ instruments | Elixir developers building concurrent, fault-tolerant applications. | | dukascopy-fx | Rust | High-performance fetcher with incremental updates and CLI tool | Developers needing maximum performance in a Rust environment. | | Tickstory | GUI Software | Downloads tick data for use in MetaTrader 4/5 | MT4/MT5 users who want to backtest their EAs with high-quality data. |
Be aware of how your backtesting model handles weekend gaps, as this can affect performance calculations. Conclusion
Select your formatted CSV file and map the columns (Time, Bid, Ask, Volume). Python (Pandas & Backtesting.py)
Data is organized in a strict URL directory structure based on UTC time:
