Dukascopy Historical Data Best Link

When decompressed, each individual tick consists of a 20-byte binary struct containing five 32-bit big-endian integers:

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: User reports from the Dukascopy support board indicate occasional data corruption or anomalies. For example, one user found that the close price of a previous bar retrieved via the IHistory API was incorrect when queried via onTick() , while the next bar's open price was correct. While such issues are often resolved, they serve as a reminder to always verify critical data points. dukascopy historical data

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Always test your data integrity by comparing a downloaded CSV’s daily high/low with a free source like Investing.com. Minor discrepancies can occur, but major gaps should be investigated before backtesting. When decompressed, each individual tick consists of a

Using high-frequency data to calculate realized volatility more accurately. Best Practices for Handling the Data

Because the data comes from the SWFX marketplace (aggregating liquidity from 15+ banks), the historical quotes include real bid/ask spreads. This is vital for backtesting. If you test a strategy using "fixed spreads," you might be profitable, but fail in live markets with variable spreads. Dukascopy historical data allows you to simulate slippage and spread widening during high-impact news events (like NFP or FOMC). While such issues are often resolved, they serve

🔹 – Forex, indices, commodities, crypto, and even bond futures. All with bid/ask spreads preserved.

When decompressed, each individual tick contains five key data points:

Milliseconds elapsed since the start of the current hour.