Dow Jones (US30) Historical Data CSV Free Download

US30 Historical Data — Timeframe Breakdown

M1, M5 and M15 contain the most recent 100,000 candles (the MetaTrader 5 terminal window). M30 and above carry the full broker history since July 2019.

CSV Columns Explained

How to Use the US30 Data

1. Download the ZIP and extract the nine CSV files.
2. For MT5: import into the Strategy Tester or rebuild the US500 symbol history; match the exact symbol name your broker uses (US500, SPX500, SP500, USA500).
3. For Python: load with pandas, parse the Timestamp column, sort ascending and build features (returns, range, session flags).
4. Run a data-quality pass first: duplicate timestamps, OHLC violations and session gaps are the three checks that catch most bad imports.
5. Include spread and the overnight financing behavior when you interpret results — index CFDs are not futures.

import pandas as pd

df = pd.read_csv("US30m_PERIOD_M30_OHLC.csv")
df["Timestamp"] = pd.to_datetime(df["Timestamp"])
df = df.sort_values("Timestamp").set_index("Timestamp")

df["range"] = df["High"] - df["Low"]
df["body"]  = (df["Close"] - df["Open"]).abs()
df["session"] = pd.cut(df.index.hour, bins=[-1, 7, 13, 21, 24],
                       labels=["Asia", "London", "NewYork", "LateNY"])

print(df.tail())
print(df[["range", "body", "TickVolume", "Spread"]].describe())

Also Known As

US30 is listed under several broker names: DJ30, WS30, DJIA, USA30, Dow Jones Index CFD. The dataset works with any of them — rename the symbol to match your MT5 Market Watch exactly.

US30 Historical Data — FAQ

What is the difference between US30 and the real Dow Jones?

US30 is the broker CFD that tracks the Dow Jones Industrial Average. Prices follow the cash index during market hours with a small spread and financing adjustments overnight. Use this dataset when you backtest the same US30 symbol you trade.

Does the data include the 2020 crash?

Yes — February and March 2020 are fully included from M30 up to Monthly. That makes this file ideal for gap-risk and stop-distance stress tests.

Can I open these CSVs in Excel?

Yes. Every file is plain comma-separated OHLCV data with a header row: Timestamp, Open, High, Low, Close, TickVolume, Spread. Excel, Google Sheets, pandas and R all read it without conversion.

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