BTCUSDT (Bitcoin / Tether (USDT)) Historical Data CSV Free Download

BTCUSDT 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 .

CSV Columns Explained

How to Use the BTCUSDT Data

1. Download the ZIP and extract the nine CSV files.
2. For MT5: import the CSVs into a custom symbol (Market Watch → Symbols → Create Custom Symbol → Import Bars) — this works for live and delisted symbols alike — or use them for offline analysis.
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 unexpected gaps are the three checks that catch most bad imports.
5. Remember crypto trades weekends — treat weekend candles as real liquidity, not as noise, when calibrating stops.

import pandas as pd

df = pd.read_csv("BTCUSDTm_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["ret"]   = df["Close"].pct_change()

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

Also Known As

BTCUSDT is listed under several names depending on the broker: BTCUSDT, BTC/USDT, Tether-margined Bitcoin. The dataset works with any of them — rename the files or the custom symbol to match your MT5 Market Watch exactly.

BTCUSDT Historical Data — FAQ

How far back does the BTCUSDT data go?

BTCUSDT data spans May 2026 – Oct 2026 overall. M30, H1, H4, D1, W1 and MN1 hold the full broker history; M1, M5 and M15 contain the most recent 100,000 candles each (the MT5 terminal window). All files end with the latest bar at export time — 19 October 2026.

Which MT5 symbol name does this dataset use?

The files are exported from the BTCUSDTm symbol (broker “m” suffix). Rename them to match your own broker’s symbol — BTCUSDT, BTC/USDT, Tether-margined Bitcoin. The CSV structure (Timestamp, Open, High, Low, Close, TickVolume, Spread) is identical across brokers.

Can I use this data for MT5 backtesting and machine learning?

Yes. Every file is plain CSV: Timestamp, Open, High, Low, Close, TickVolume, Spread. Crypto trades 24/7 including weekends, so the series has no session gaps — a clean input for pandas, XGBoost/LSTM pipelines and MT5 custom-symbol backtests.

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