How to Download Historical Data for Backtesting (MT5 and Free OHLC Sources)

Why Data Quality Kills More Backtests Than Bad Indicators

Garbage in, garbage out is the oldest cliché in quantitative trading, and it holds up. Backtesting with survivorship-biased, split-unadjusted, or vendor-corrupted data produces numbers that look fine on paper and collapse in live trading.

IndicatorEdge ran 660,005 out-of-sample backtests across 903 assets and four timeframes — 1-Hour, 4-Hour, Daily, and Weekly — using cost-adjusted OHLCV data with realistic spread and commission assumptions. The methodology page covers the full pipeline. What follows is a practical guide to sourcing comparable data yourself so you can verify or extend any result you see here.

The two most common failure modes are survivorship bias (your universe only contains assets that survived, so historical returns look better than they were) and price adjustment errors (stock splits and dividends that are not accounted for turn a clean signal into noise). Fix both before you run a single backtest.

Downloading Historical Data from MetaTrader 5

MT5's built-in History Center is the fastest starting point for forex and CFD data if your broker runs MT5. Open it from Tools → History Center, select a symbol, pick a timeframe, and click Download. MT5 pulls whatever your broker stores server-side.

To export bars you can use outside MT5, write a short MQL5 script that calls CopyRates() and writes the result to a CSV with FileWrite(). That is roughly 15–20 lines and gives you a clean OHLCV file in any directory you choose.

The practical ceiling is broker-side storage: most retail MT5 brokers keep only 2–5 years of sub-daily bar history. If you need a longer window — or coverage of assets your broker does not offer — you will need an external source.

Also strip weekend gaps and DST-shift artifacts before running any logic. They appear consistently in forex feeds when a broker's server rolls over on Sunday and are not real price action.

Free OHLCV Sources Worth Knowing

Dukascopy Historical Data — tick and OHLCV data for major forex pairs and some indices going back many years on select instruments. The download interface is dated but functional. Useful when you need long forex history at 1-minute or tick granularity.

HistData.com — 1-minute ASCII CSVs for a focused set of forex pairs, clean column format, free download. Practical if forex is your entire universe and you do not want to deal with an API client.

Yahoo Finance via the yfinance Python library — split-and-dividend-adjusted OHLCV for US equities, ETFs, and major indices. The free tier returns daily bars going back decades. Intraday history on the free tier is limited to recent weeks.

Stooq.com — daily data for a broad international universe including markets underrepresented by US-centric sources. CSV downloads require no account.

Exchange public REST APIs (crypto) — Binance, Coinbase, and Kraken all expose unauthenticated endpoints that return OHLCV candles at multiple granularities back to each exchange's launch date. No API key required for historical data pulls.

Whichever source you use, spot-check a handful of bars against a second source before trusting a full dataset. One-off feed errors are common and easy to miss until a backtest produces an obviously wrong spike.

Resolution and What Actually Matters for Your Backtest

A common assumption is that 1-minute data produces more accurate backtests than hourly or daily data. The answer depends entirely on the timeframe your signal lives on.

For strategies that trigger on daily RSI crosses, weekly pivot levels, or 4-hour moving average alignments, daily or weekly bars are the correct input — not a compromise. IndicatorEdge tests only 1-Hour, 4-Hour, Daily, and Weekly timeframes, and across those, roughly 63% of best indicator-asset combinations beat buy-and-hold, with a median best Sharpe of 0.62 across 903 assets. Those results were not produced from tick data because the signals do not require it.

Higher-resolution data introduces its own problems: larger files, longer runtimes, and heavier exposure to microstructure noise — bid-ask bounce, zero-volume bars during off-hours, and data-feed-specific quirks that disappear at daily aggregation. A backtest built on 1-minute bars can show high win rates that evaporate in execution because slippage and spread represent a far larger share of the trade at that granularity.

Match your data resolution to your signal. If your entry criterion fires on a sub-hour bar, you need sub-hour data and an honest spread model. If it fires on a daily close, daily data is correct and sub-minute data adds noise without adding information.

IndicatorEdge does not test sub-hourly signals. All published results are on 1-Hour, 4-Hour, Daily, and Weekly bars — the timeframes where signals have enough bar-to-bar independence to generalize across a large, diverse asset universe.

These Are Hypothetical Backtests — Not Advice

Every result on IndicatorEdge — including all 660,005 backtests across 903 assets — is hypothetical and backward-looking. Backtests include realistic cost assumptions (spread, commission, slippage), but no backtest can fully capture every live-trading variable: liquidity gaps, broker rejection, connection failures, or execution timing in fast markets.

Past backtest performance does not guarantee future results. Nothing on this site is financial advice. The methodology is published openly precisely so you can source comparable data, run your own verification, and decide for yourself whether a result holds. If a number looks suspiciously good, test it on fresh data. That is the whole point of the transparency here.