Dukascopy Historical Data Exclusive

: Access history for over 1,600 instruments , including Forex majors/minors, Commodities, Indices, Stocks, ETFs, and even Crypto CFDs.

To get started with this exclusive data, follow this technical workflow:

Select your date range (e.g., January 1, 2015, to the present date).

Data is only as good as how you use it. Follow these principles to maximize your backtesting accuracy. Account for Swaps and Slippage dukascopy historical data exclusive

For a quick download of a specific instrument and timeframe, the web-based tool is perfect. It provides data in .csv and .hst formats from tick-by-tick up to monthly intervals.

Precious metals (Gold, Silver, Platinum), Energy (Crude Oil, Brent, Natural Gas), and agriculture.

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. : Access history for over 1,600 instruments ,

Set the export timezone to match your backtesting platform (typically UTC or New York GMT+2/GMT+3 with DST). Step 3: Export to Your Trading Architecture

Set the generated .fxt files to "Read-Only" in your Windows file properties. This prevents MetaTrader from overwriting your high-quality data with its standard, lower-quality history.

If you are importing this data into MT4, remember that MT4 usually operates on a fixed GMT offset (like GMT+2). Dukascopy data is native Precious metals (Gold, Silver, Platinum), Energy (Crude Oil,

Major digital assets mapped against fiat currencies.

But what makes Dukascopy historical data so special? The answer lies in three words:

# pip install dukascopy-tick-downloader numpy pandas lzma from dukascopy_tick_downloader import DukascopyTicker import pandas as pd