Datasets:

Rogendo
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forex-dukas-copy

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Forex Dukas Long-History Market Data

Dataset Summary

Historical market data collected from Dukascopy and organized for time-series machine-learning experiments.

The dataset is intended primarily for research into:

time-series forecasting
financial representation learning
transformer-based forecasting
PatchTST-style architectures
multi-task learning
directional classification
return forecasting
volatility forecasting
cross-asset learning

Assets

The dataset currently contains historical data for:

XAUUSD
EURUSD
GBPUSD
EURGBP
USDJPY

Timeframes

Available timeframes include:

1 minutes
5 minutes
15 minutes
30 minutes
1 hour
4 hours

Data Format

The raw market data contains OHLCV-style information:

timestamp
open
high
low
close
volume

Data Organization

The repository contains raw and split data organized by:

asset → timeframe → temporal chunks

This organization is intended to make large-scale training experiments easier without requiring the entire historical dataset to be loaded into memory at once.

Intended Research Use

This dataset is intended for experimental financial machine-learning research.

Potential applications include:

Single-task forecasting
Multi-task forecasting
Transformer time-series models
Cross-asset representation learning
Foundation-model-style pretraining
Directional classification
Future-return prediction
Future-price prediction
Volatility prediction

Important Considerations

Financial markets are non-stationary and historical predictive relationships may disappear over time.

Performance on historical data should not be interpreted as evidence of future trading profitability.

Experiments should use strictly chronological train/validation/test splits and avoid look-ahead leakage.

Citation / Source

Source: Dukascopy historical market data.

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