Dukascopy Historical Data Free Jun 2026

Whether you are a retail trader refining a manual strategy or a quant developer building a high-frequency bot, Dukascopy's data feed provides the backbone for accurate backtesting and market analysis. Why Traders Choose Dukascopy Data

The Ultimate Guide to Dukascopy Historical Data: Downloading, Processing, and Backtesting

The data is aggregated from multiple liquidity providers, giving it institutional-grade depth.

Access history for dozens of Forex majors, minors, and exotics, alongside major stock indices, commodities (Gold, Silver, Crude Oil), and even cryptocurrencies. dukascopy historical data

function to import downloaded CSV files directly into a spreadsheet. Dukascopy Bank SA Usage Considerations Forex Historical Data Feed :: Dukascopy Bank SA

const getHistoricalRates = require('dukascopy-node'); (async () => const data = await getHistoricalRates( instrument: 'btcusd', dates: from: new Date('2019-01-13'), to: new Date('2019-01-14') , timeframe: 'tick', format: 'json' ); console.log(data); )();

(Third-party tools)

For those looking to explore this data, it's highly recommended to utilize a reliable, consistent source for reliable backtesting and analysis.

: Data typically stretches back to 2003–2006, depending on the currency pair. Modeling Quality : Using tick data allows for 99% modeling quality

Access real tick data (bid/ask) and minute-level data. Whether you are a retail trader refining a

Historical data from Dukascopy enables a wide range of trading and analytical activities.

For custom Python backtesting, you should aggregate the raw ticks into Open-High-Low-Close (OHLC) bars to save memory and processing time.

For analysts and data scientists who prefer Python, a rich ecosystem of open-source libraries has been built around downloading and processing Dukascopy data. These libraries simplify the process of fetching data and loading it directly into , the industry standard for data analysis. function to import downloaded CSV files directly into