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ASX 200 (AUS200) Historical Data CSV Free Download

AUS200 opens the global trading day, so it often leads the tone other indices follow. It is also the index with the biggest gap risk relative to its session hours, which makes it a favorite for gap-fade and overnight-breakout research. The full 2019-2026 daily and M30/H1 history is included.

433,682

OHLC candles across 9 timeframes.

M1 → MN1

Nine separate CSV files in one ZIP.

Jul 2019 – Oct 2026

Includes the 2020 crash and 2022 bear market.

CSV

Timestamp, Open, High, Low, Close, TickVolume, Spread.

6.24 MB

ZIP size, plain uncompressed CSV inside.

AUS200m

MT5 export symbol — rename to match your broker.

AUS200 Historical Data — Timeframe Breakdown

FileRowsFromTo
AUS200m_PERIOD_M1_OHLC.csv100,0002026-06-252026-10-09
AUS200m_PERIOD_M5_OHLC.csv100,0002025-04-112026-10-09
AUS200m_PERIOD_M15_OHLC.csv100,0002022-03-222026-10-09
AUS200m_PERIOD_M30_OHLC.csv79,0812019-07-162026-10-09
AUS200m_PERIOD_H1_OHLC.csv40,8112019-07-162026-10-09
AUS200m_PERIOD_H4_OHLC.csv11,1142019-07-162026-10-09
AUS200m_PERIOD_D1_OHLC.csv2,2122019-07-162026-10-09
AUS200m_PERIOD_W1_OHLC.csv3772019-07-142026-10-04
AUS200m_PERIOD_MN1_OHLC.csv872019-07-012026-10-01

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

ColumnMeaningBacktesting Note
TimestampBroker candle open time (server time).Verify the server offset before aligning with another data source.
Open, High, Low, CloseUS500 candle prices.Validate High ≥ max(Open, Close) and Low ≤ min(Open, Close).
TickVolumeBroker tick activity inside the candle.Not centralized volume — use it as an activity proxy.
SpreadRecorded broker spread.Keep it: index CFDs widen at the cash open and rollover.

How to Use the AUS200 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("AUS200m_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

AUS200 is listed under several broker names: ASX200, AUS200Cash, S&P/ASX 200 Index CFD. The dataset works with any of them — rename the symbol to match your MT5 Market Watch exactly.

AUS200 Historical Data — FAQ

Is AUS200 the price index or the accumulation index?

AUS200 tracks the S&P/ASX 200 price index (not the accumulation index that reinvests dividends). Broker CFDs track the price index, so this data matches what you actually trade in MT5.

Why does AUS200 have so many gaps in the data?

The Australian session closes while US markets trade. Overnight US moves create opening gaps in AUS200. The gaps are real market behavior — keep them in your backtest instead of smoothing them out.

What date range is included?

M30, H1, H4, D1, W1 and MN1 cover July 2019 to October 2026. M1, M5 and M15 contain the most recent 100,000 candles each, matching the MT5 terminal limit.

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