Dukascopy+historical+data

With bid/ask tick data, you can simulate realistic order fills. For example: "If my signal triggered at 10:00:05.123, what was the actual spread and available depth?"

Far superior to daily or hourly data, tick-level data lets you model slippage, spreads, and order fills realistically — crucial for high-frequency or scalping strategies.

Download the 1-minute data around NFP (Non-Farm Payroll) releases. By isolating the 1-minute bar containing the 8:30 AM news release, you can quantify the average slippage and volatility spike. This tells you exactly how wide your stop loss needs to be during news events. dukascopy+historical+data

For developers and quants, manually clicking JForex for 20 instruments is not feasible. The community has built Python libraries specifically to interface with Dukascopy’s public servers.

The most popular tool is dukascopy-tick-downloader (available on GitHub). Using a simple Python script, you can replicate a decade of history in minutes: With bid/ask tick data, you can simulate realistic

# Example pseudo-code
from dukascopy import Dukascopy
downloader = Dukascopy()
data = downloader.get_instrument_history(
'EUR/USD',
'tick',
'2010-01-01',
'2023-01-01'
)
data.to_csv('eurusd_10_years_ticks.csv')

Pros: Blazing fast, programmatic, allows for automatic re-downloads. Cons: Requires coding knowledge (Python). Unofficial; Dukascopy does not provide support for third-party scrapers.

Analyze price action around NFP (Non-Farm Payroll), FOMC minutes, or COVID-19 flash crashes. Tick data reveals the micro-structure of panic. Pros: Blazing fast

Dukascopy provides the JStore application, their native platform for historical data visualization and download.