That trading volume you see? 70-95% is fake. Wash trading, self-dealing, and manufactured volume make reported data meaningless.
Hypothesis HY10035
That trading volume you see? 70-95% is fake. Wash trading, self-dealing, and manufactured volume make reported data meaningless.
Trading hypothesis
What traders get wrong
False assumption:
"Trading data is accurate."
Truth:
Trading data is fake. 70-95% of reported volume on many exchanges is wash trading.
Problem for trader:
You can't trust volume. You can't trust order books. Price discovery is compromised.
Key takeaways
What you should consider as a trader
- Most volume is fake - Bitwise study showed 95% of volume was fake.
- Wash trading is incentivized - Exchanges want to appear liquid.
- No enforcement - Offshore exchanges face no consequences.
- Real volume is much lower - Adjust expectations accordingly.
- Credible volume exists - Some exchanges have real volume.
Data you need
Identify real vs fake volume
Data points:
- Volume authenticity score by exchange
- Wash trade detection
- Credible volume estimate
- Exchange credibility tier
Comparison of data sources
Where to get crucial data feeds
| Source | Availability | Notes |
| CoinMarketCap | ⚠️ Partial | Raw volume, some adjustments. |
| Kaiko | ⚠️ Partial | Better data quality, expensive. |
| **Madjik** | ✅ Yes | 🚀 Get API Access Now |
Available metrics for this hypothesis:
| Metric | Description | Change dimensions | Time dimensions | How to use | API spec |
| `ME10003` | Volume analysis | • Absolute Value (value) • Relative Change (relchg) • Score 0-100 (score) | • Current (now) • Past 24 Hours (past24h) • Past 7 Days (past7d) | Example | API |
| `ME10006` | Exchange health | • Absolute Value (value) • Relative Change (relchg) • Score 0-100 (score) | • Current (now) • Past 24 Hours (past24h) • Past 7 Days (past7d) | Example | API |
Clean data for AI, A2A, MCP, etc.
Science behind hypothesis
Research supports this hypothesis
Bitwise report to SEC showed 95% of reported Bitcoin volume was fake.
Bottom line
Real volume is a fraction of reported volume. Filtering wash trading helps you see actual market activity. Madjik's volume authenticity scores separate real trading from manufactured numbers, giving you honest liquidity assessment.
Practical use
How to use this data in trading:
Combine these metrics for comprehensive analysis:
- ME10003 (Volume Analysis): Filter wash trading to size positions correctly and detect genuine fiat inflows confirming trends.
- ME10006 (Exchange Health): Monitor exchange solvency and withdrawal status to manage counterparty risk before problems emerge.
Detailed examples with Python code, AI agent integration (MCP/A2A), and risk analysis:
| `ME10003` | Volume Analysis Trading Guide | Example → |
| `ME10006` | Exchange Health Trading Guide | Example → |
API Documentation: docs.madjik.io
For informational purposes only. Not financial, investment, tax, legal or other advice.