What columns are in the CSV file?

OHLC files contain timestamp, open, high, low, close and (where available) volume. Tick files contain timestamp, bid, ask and bid/ask volume. Timestamps are UTC.

Are the timestamps in UTC?

Yes. Timestamps are in UTC, so data lines up consistently across instruments and sessions regardless of your local timezone.

Can I load the data into pandas?

Yes. Use pandas.read_csv with parse_dates on the timestamp column. The JSON export also loads directly with pandas.read_json or json.load.

Is the data bid or ask price?

You choose. Both bid and ask are available; select the side you need at download time. Tick exports include both bid and ask on every row.

Historical Market Data CSV & JSON Format Explained

By Martin Buessler · Published 22 June 2026 · Updated 1 August 2026 · 1 min read

Before you run a download, it helps to know exactly what you're getting. Here's the column layout the MarketData Hub client writes for both OHLC candles and raw tick data — plus how to load the files into the most common tools.

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OHLC candle CSV

Candle exports (1-minute through monthly) use one row per bar with a UTC timestamp and the four classic price fields, plus volume where available:

timestamp,open,high,low,close,volume
2024-01-02 00:00:00,1.10423,1.10489,1.10401,1.10455,1843.0
2024-01-02 00:01:00,1.10455,1.10472,1.10440,1.10461,1210.0

open is the first price of the bar, high/low the extremes, and close the last price. You choose bid or ask prices at download time.

Tick CSV

Tick exports record every quote, so there is no open/high/low/close — just the timestamp (to the millisecond) with bid and ask:

timestamp,bid,ask,bidVolume,askVolume
2024-01-02 00:00:00.123,1.10423,1.10425,1.5,2.0
2024-01-02 00:00:00.318,1.10424,1.10426,1.0,1.2

JSON format

The same data is available as JSON — an array of objects with the same keys — if you'd rather not parse CSV in code.

Import into Excel or Google Sheets

CSV opens directly. Use Data → From Text/CSV (Excel) or File → Import (Sheets) and the columns map automatically.

Import into Python (pandas)

import pandas as pd
df = pd.read_csv("eurusd_m1.csv", parse_dates=["timestamp"], index_col="timestamp")

Import into MetaTrader, NinjaTrader & TradingView

The CSV layout matches what MetaTrader's History Center, NinjaTrader and most charting platforms expect; map the timestamp and OHLC columns in their import dialog. Ready to grab a file? Open EUR/USD or browse all instruments.

Frequently asked questions

What columns are in the CSV file?: OHLC files contain timestamp, open, high, low, close and (where available) volume. Tick files contain timestamp, bid, ask and bid/ask volume. Timestamps are UTC.
Are the timestamps in UTC?: Yes. Timestamps are in UTC, so data lines up consistently across instruments and sessions regardless of your local timezone.
Can I load the data into pandas?: Yes. Use pandas.read_csv with parse_dates on the timestamp column. The JSON export also loads directly with pandas.read_json or json.load.
Is the data bid or ask price?: You choose. Both bid and ask are available; select the side you need at download time. Tick exports include both bid and ask on every row.