94+ Datasets Ready · FX · Crypto · Gold · Stocks · Bonds

What Will You Build
With 26 Years of Market Data?

Your ideas deserve real data.

Whether you're testing your first trading idea or training a machine learning model on 330 million bars — MARKETDPRO gives you professionally cleaned, indicator-enriched datasets ready to use from day one. Buy once. Download. Own forever. For research and backtesting purposes only — not financial advice.

Browse Data Catalog → See What's Possible ↓

No subscription · One-time purchase · Instant download

WHAT CAN YOU DO WITH THIS DATA?

From Your First Chart to Your First Algorithm.

You don't need to be a developer. You don't need a finance degree. You just need curiosity — and data that actually works.

🅣 BEGINNER
"I want to see what gold did during the 2008 crash."
Download XAUUSD D1. Open it in Excel or Google Sheets. Scroll to 2008. That's it. You're already doing research that used to cost thousands of dollars.
No coding required · Works in Excel, Google Sheets, Numbers
# Just open the CSV in Excel
date      | open   | close
2008-09-15 | 783.40 | 768.20
2008-09-16 | 768.20 | 782.50
2008-09-17 | 782.50 | 865.00
# Gold surged +12% in 3 days
⚙️ INTERMEDIATE
"I want to test if MA crossover actually works on EURUSD."
MA20 and MA50 are already in every row. No calculation needed. Load the Parquet in Python, write 10 lines, and you have a 20-year backtest in seconds. Results for research only.
Python · pandas · 10 lines of code · Full guide →
import pandas as pd
df = pd.read_parquet('EURUSD_D1.parquet')
# MA20 and MA50 already there
df['signal'] = df.ma20 > df.ma50
df['ret'] = df.close.pct_change()
result = df[df.signal].ret.mean()
# Research use only. Not advice.
🚀 ADVANCED
"I want to train a model on 40 FX pairs across 20 years."
330M+ bars. 40 pairs. M1 resolution. All in the same schema. Stack them in DuckDB, run feature engineering in polars, feed into your model. The data pipeline is already done.
DuckDB · polars · PyTorch / sklearn · Full guide →
import duckdb
db = duckdb.connect()
db.execute("""
  SELECT * FROM
  read_parquet('fx/**/*.parquet')
  WHERE rsi14 < 30
""")
# 40 pairs. 20 years. One query.
🤔 WAIT, YOU CAN ALSO…
Discover hidden patterns
Does Gold always rise when the dollar falls? Check it. 26 years of data. For research only.
Build a personal dashboard
Feed the data into TradingView Pine Script, Grafana, or your own web app. The schema never changes.
Study historical crises
2008, COVID crash, FTX collapse, SVB bank run — all in the data. Build a crisis playbook.
Teach yourself algo trading
No live money. No broker API. Just data, Python, and your ideas. The safest way to learn.
See Full How-to Guide with Examples →

All use cases are for research and backtesting purposes only. Not financial advice.

What is MARKETDPRO?

We do the hard part so you don't have to. Raw data is messy, incomplete, and hard to trust. Every MARKETDPRO dataset has been through a 4-step process before it reaches you.

📥
1 — Collect
Raw OHLCV from institutional-grade sources. Up to 26 years of history per asset.
🔧
2 — Clean
Remove outliers, fill verified gaps, validate every OHLC row. Each dataset passes a QC score gate before release.
📊
3 — Enrich
MA20/50/100/200, ATR14, RSI14, RSI zone — pre-calculated on every single bar. Ready to use instantly.
📦
4 — Deliver
Parquet + CSV. Pay once, download instantly. Your file, your machine, yours forever.
94+ Datasets Available
26yr Historical Depth
330M+ Total Bars Collected
M1→D1 All Timeframes

What's in the Catalog

Five asset classes. One consistent schema. All with indicators included.

FX · FOREX
40 pairs · M1 to D1
EURUSD, GBPUSD, USDJPY…
History from 2003
Backtest FX strategies · Study market structure · Analyze session volatility patterns
CRYPTO
12 assets · M1 to D1
BTCUSD, ETHUSD, SOLUSD…
From exchange launch
Study crypto cycles · Test momentum strategies · Analyze BTC halving impacts
GOLD · SILVER
XAUUSD, XAGUSD · M1 to D1
From 2003 · 1-minute precision
Analyze safe-haven behavior · Study inflation correlation · Test range strategies
US STOCKS · ETFs
43 symbols · D1
AAPL, MSFT, NVDA, SPY, QQQ…
Split & dividend adjusted · 2000+
Backtest equity strategies · Build factor models · Study earnings season patterns
BONDS · MACRO
US Treasuries (2Y/10Y/30Y)
Fed Funds, CPI, VIX, Nonfarm
From 1962
Study yield curve inversions · Analyze rate cycle impacts · Build macro dashboards
More Coming
EU stocks · ASX · Commodities
Added as data is verified
View Full Catalog →

The Format Quants Actually Use

Every dataset ships with metadata.json (QC scores, date range, bar count) and a README.md explaining every column in plain English.

time  ·  open · high · low · close  ·  volume
ma20 · ma50 · ma100 · ma200
atr14  ·  rsi14  ·  rsi14_zone

# Format: Parquet (snappy) + CSV where applicable
# Works with: pandas · polars · DuckDB · R · Julia · Excel

Free sample available for every dataset. See the data before you buy.

Your next research project starts here.

94+ datasets. Five asset classes. 26 years of history. One consistent format. All for research purposes — not financial advice.

Open Data Catalog → How to Use the Data →

One-time purchase · Instant download · No subscription required