Dukascopy Historical Data Exclusive ((exclusive)) Jun 2026

Unlike many brokers that only provide bar data (M1, H1), Dukascopy offers tick-by-tick quotations . This allows for a 99.9% modeling quality in backtests, which is critical for scalping or high-frequency strategies .

The Data Edge: Why Serious Traders Choose Dukascopy Historical Data dukascopy historical data exclusive

import struct import lzma # After downloading the .bi5 file from the Dukascopy URL with lzma.open("hour_ticks.bi5", "rb") as f: while True: data = f.read(20) # Each tick struct is exactly 20 bytes if not data: break # Unpack: TimeOffset(I), Ask(I), Bid(I), AskVol(f), BidVol(f) time_offset, ask, bid, ask_vol, bid_vol = struct.unpack(">IIIff", data) # Convert integer prices to floating-point values actual_ask = ask / 100000.0 actual_bid = bid / 100000.0 Use code with caution. Unlike many brokers that only provide bar data

: The data includes both bid and ask prices , which is critical for accurate spread calculation and realistic back-testing. Historical coverage often extends back over 15 years for major currency pairs. : The data includes both bid and ask

In the world of algorithmic trading and quantitative analysis, the mantra is simple: your model is only as good as your data. While many brokers provide basic historical charts, savvy traders consistently turn to as the "gold standard" for backtesting.

The most praised aspect of Dukascopy's offering is its raw, tick-by-tick data. While many sources only offer OHLCV (Open, High, Low, Close, Volume) data, Dukascopy provides a much deeper level of detail, making it a critical resource for high-frequency and algorithmic systems.

The community and open-source developers have built a robust ecosystem around Dukascopy's data. A vibrant ecosystem of open-source libraries has sprung up, providing: