Dukascopy Historical Data Exclusive ((hot)) -

If you are serious about backtesting, you’ve likely realized that the quality of your data is just as important as the logic of your strategy.

Common file formats and delivery

ZIP archives with CSV files (CSV is the most common).
CSV columns typically: timestamp (ISO or Unix ms), bid, ask, [volume].
Filenames encode instrument and timeframe (e.g., EURUSD_ticks_YYYYMMDD.zip or EURUSD_M1.zip).

Access to years of data across FX, Commodities, and Indices. How to Get It (The Pro Way) dukascopy historical data exclusive

, this data feed offers a level of transparency and granularity that most retail brokers simply cannot match Why "Exclusive" Data Matters What makes Dukascopy’s data truly stand out is its tick-by-tick precision If you are serious about backtesting, you’ve likely

What Dukascopy historical data contains

Tick, 1‑minute, 1‑hour, and daily price data for FX pairs, metals, cryptocurrencies, indices, and some CFDs.
Bid and ask where available; many files include both or only one depending on instrument/type.
Volume (tick/quote counts) and spread information in some datasets.
Timestamps usually in UTC.

9. Quick Reference: Symbol Mapping

| Instrument | Symbol in Dukascopy | |------------|----------------------| | EUR/USD | EURUSD | | Gold (spot) | XAUUSD | | Bitcoin | BTCUSD | | US 30 Index | US30 | | Apple stock | AAPL (limited history) | ZIP archives with CSV files (CSV is the most common)

5. Working with Exclusive Fields

Spread analysis example

df['spread_pips'] = df['spread'] * 10000  # for EURUSD
print("Avg spread (ticks):", df['spread_pips'].mean())
print("Spread std dev:", df['spread_pips'].std())

2. Data Access Methods

Method A: Official Dukascopy Historical Data Feed (JForex)

Exclusive for funded accounts / API users