foxhunt/wave153_bakeoff_cryptodatadownload/QUICK_REFERENCE.md

CryptoDataDownload - Quick Reference Card

🎯 Bottom Line

Score: 8.0/10 ⭐⭐⭐⭐ Verdict: ✅ RECOMMENDED for production use

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📥 Download URLs

# BTC/USD (44 MB)
curl -o btc_2024.csv https://www.cryptodatadownload.com/cdd/Bitstamp_BTCUSD_2024_minute.csv

# ETH/USD (46 MB)
curl -o eth_2024.csv https://www.cryptodatadownload.com/cdd/Bitstamp_ETHUSD_2024_minute.csv

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📊 Key Metrics

Metric	BTC/USD	ETH/USD
Completeness	96.65%	98.03%
OHLCV Violations	0	0
Outliers	0	0
Zero Volume	3.34%	11.26%
Price Range	$38K-$108K	$2.1K-$4.1K
Total Rows	509,364	516,678

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✅ Strengths

• Zero data integrity issues (perfect OHLCV)
• No extreme outliers (>10% moves)
• Free & no API key required
• Full 2024 coverage (366 days)
• Daily updates

⚠️ Weaknesses

• 11% zero-volume bars (ETH)
• 3-4% data gaps
• Single exchange (Bitstamp only)
• No real-time API
• Manual download required

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💻 Python Quick Start

import pandas as pd

# Load data (skip header row)
df = pd.read_csv('Bitstamp_BTCUSD_2024_minute.csv', skiprows=1)
df['date'] = pd.to_datetime(df['date'])
df = df.sort_values('date')  # Chronological order

# Handle gaps (forward-fill)
df = df.set_index('date').asfreq('1min', method='ffill').reset_index()

# Filter zero-volume bars (optional)
df_filtered = df[df['Volume BTC'] > 0]

print(f"Total bars: {len(df):,}")
print(f"Date range: {df['date'].min()} to {df['date'].max()}")

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🦀 Rust Integration

// Convert to Parquet for Foxhunt
use crate::data::parquet_persistence::ParquetMarketDataWriter;

let writer = ParquetMarketDataWriter::new(
    "test_data/bitstamp_btcusd_2024.parquet"
);

// Write OHLCV bars
for bar in csv_reader.into_iter() {
    writer.write_event(MarketDataEvent::from_ohlcv(bar)).await?;
}

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📝 Data Format

unix,date,symbol,open,high,low,close,Volume BTC,Volume USD
1704067200,2024-01-01 00:00:00,BTC/USD,42258,42268,42257,42268,1.049735,44361.10698

Notes:

• Header row: website URL (skip it!)
• Reverse chronological (newest first)
• Unix timestamps + human-readable dates
• Separate volume columns (crypto + USD)

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🔍 Use Cases

Use Case	Suitability
ML Training	✅ Excellent
Backtesting	✅ Excellent
Research	✅ Excellent
Production Signals	⚠️ Good (handle gaps)
Real-time Trading	❌ Not suitable (no API)
Multi-exchange Arb	❌ Not suitable (single source)

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📂 File Locations

/home/jgrusewski/Work/foxhunt/wave153_bakeoff_cryptodatadownload/
├── Bitstamp_BTCUSD_2024_minute.csv (44 MB)
├── Bitstamp_ETHUSD_2024_minute.csv (46 MB)
├── analysis_report.json            (detailed metrics)
├── BAKEOFF_SUMMARY.md             (full report)
└── QUICK_REFERENCE.md             (this file)

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🚀 Next Steps

1. ✅ Data downloaded and validated
2. ⏭️ Convert to Parquet format
3. ⏭️ Integrate with backtesting_service
4. ⏭️ Train ML models on historical data
5. ⏭️ Compare to alternative data sources

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Last Updated: 2025-10-12 Analysis: Wave 153 Data Source Bake-Off