💡 Always download both Bid and Ask data. Testing only on the "Close" price ignores the spread, which is the number one reason why "profitable" bots fail when they go live.
Includes accurate bid/ask quotes and volume metrics down to the millisecond.
stands out as a premier resource for traders looking for high-quality, free tick-level data. Whether you are a retail trader refining a scalping strategy or a quant developing complex machine learning models, the data provided by Dukascopy can help you understand market dynamics, improve your trading profitability, and build more robust algorithmic systems. dukascopy+historical+data
Researchers and algorithmic traders use Dukascopy data for various, complex tasks:
This comprehensive guide covers how to download, process, and utilize Dukascopy historical data to build robust trading strategies. Why Choose Dukascopy Historical Data? 💡 Always download both Bid and Ask data
For backtesting, this is critical. Most strategies look great on 1-minute data but fall apart in real life because of spread widening during news events or low liquidity. Because Dukascopy provides tick data, you can see the exact spread at every second of the day. This allows for "Tick Data Suite" level backtesting without having to pay thousands of dollars for premium data feeds from vendors like Tick Data Suite or dukascopy.
Open MT4, go to > History Center (F2), select your currency pair, and delete all existing broker data. Close MT4. Open a tool like Tickstory or QuantDataManager . stands out as a premier resource for traders
Most retail forex platforms provide "Minute Data" (Open, High, Low, Close for a one-minute interval). While sufficient for swing trading, this is insufficient for high-frequency trading (HFT) or scalping strategies.
You can retrieve historical data through three primary methods: Manual Web Tool Historical Data Feed to download files for manual backtesting. JForex Platform
Beyond Forex, the repository includes historical data for CFDs on equities, stock indices, precious metals, and energies. Understanding the Data Architecture