thomas819/eurusd-dax-calendar-data

EURUSD & DAX (M1) Price Data with Macroeconomic Event Calendar

License & Data Sourcing Notice

This dataset is released without a formal open-source license ("Unlicensed").

Data was deliberately sourced from established, reputable providers (FXOpen and Investing.com) to ensure relevance and accuracy for the underlying analysis.
The data contained in this repository originates from third-party providers and is published here for educational and academic research purposes only. The author is not the original creator of the underlying market data or economic calendar data. This dataset is not intended for commercial use.

A note on data sourcing:

• Price data (EURUSD, DAX): Sourced via the QuotesDownloader 3 application provided by FXOpen. At the time of writing, no explicit restriction on non-commercial redistribution was identified in FXOpen's publicly available Terms and Conditions. It is worth noting, however, that the underlying price feed may be subject to upstream licensing agreements between FXOpen and its own liquidity/data providers, which are not publicly disclosed. Users planning any commercial use are encouraged to verify this independently with FXOpen.

• Economic calendar data: Manually copied from the Investing.com (Fusion Media Ltd.). Investing.com's Terms of Use include restrictions on the reproduction and redistribution of their content. This data is shared here strictly for non-commercial, educational purposes; users intending broader or commercial use should consult Investing.com's Terms and Conditions directly.

Intended use: Academic research and educational purposes only. Not intended for trading, investment decisions, or any commercial application.

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Data Sources

File(s)	Source	Provider
eurusd_ask_m1.csv, eurusd_bid_m1.csv	Downloaded via QuotesDownloader 3 app	FXOpen
dax_ask_m1.csv, dax_bid_m1.csv	Downloaded via QuotesDownloader 3 app	FXOpen
calendar.csv	Manually copied from the Economic Calendar	Investing.com

• FXOpen Terms and Conditions: https://fxopen.com/legal-documents/
• Investing.com Terms and Conditions: https://www.investing.com/about-us/terms-and-conditions

Price data reflects raw bid/ask minute (M1) OHLC quotes as provided by the FXOpen quote feed.
Economic calendar data reflects event records manually copied from the Investing.com economic calendar tool.

All timestamps across all files are in GMT.

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Intended Use

The goal of this dataset is to identify and quantify the impact of macroeconomic events on the price dynamics and volatility of the DAX stock index and the EUR/USD currency pair, using event study methodology combined with GARCH volatility modeling, across four time frames (M1, M5, M15, M30).

The data window (2020-02-20 to 2026-06-30) was chosen to focus primarily on three distinct periods: the COVID-19 pandemic, the subsequent energy crisis, and the current AI era.

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Files

eurusd_ask_m1.csv / eurusd_bid_m1.csv

Minute-level (M1) OHLCV quotes for the EUR/USD currency pair.

Column	Description
date_time	Timestamp of the candle (GMT), minute resolution
open	Opening price
close	Closing price
low	Lowest price in the interval
high	Highest price in the interval
volume	Tick/trade volume in the interval

Separate bid and ask files are provided; mid-price should be computed as the average of bid and ask when spread-neutral analysis is required.

dax_ask_m1.csv / dax_bid_m1.csv

Minute-level (M1) OHLCV quotes for the DAX index (GDAXI), same column structure as above.

calendar.csv

Economic calendar events, manually copied from Investing.com.

Column	Description
Time	Date and time of the scheduled/actual event release (GMT)
Cur.	Currency/region associated with the event (e.g., USD, EUR)
Event	Name of the economic indicator/event (e.g., "US Non-Farm Payrolls", "ECB Interest Rate Decision")
Actual	Actual released value
Forecast	Consensus forecast value prior to release
Previous	Value from the previous release

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Time Coverage

All files cover the period 2020-02-20 to 2026-06-30, in GMT.

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Methodology Context (Summary)

Placeholder — to be completed upon finalization of the analysis.

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Usage Example

from datasets import load_dataset

ds = load_dataset(
    "thomas819/eurusd-dax-calendar-data",
    data_files={
        "eurusd_ask": "eurusd_ask_m1.csv",
        "eurusd_bid": "eurusd_bid_m1.csv",
        "dax_ask": "dax_ask_m1.csv",
        "dax_bid": "dax_bid_m1.csv",
        "calendar": "calendar.csv",
    }
)

Note: all CSV files use ; as the column separator.

ds_calendar = load_dataset(
    "thomas819/eurusd-dax-calendar-data",
    data_files="calendar.csv",
    sep=";"
)