When you see "BTC = $90,000", you're seeing BTC/USDT, not BTC/USD. Nobody actually pays 90,000 US Dollars - they pay Tether tokens.
Hypothesis HY10026
When you see "BTC = $90,000", you're seeing BTC/USDT, not BTC/USD. Nobody actually pays 90,000 US Dollars - they pay Tether tokens.
Trading hypothesis
What traders get wrong
False assumption:
"1 USDT = 1 USD, so prices are in dollars."
Truth:
The actual trading pair is BTC/USDT, not BTC/USD. USDT's true USD value is unknown.
Problem for trader:
If USDT is worth $0.90, BTC 'at $90k USDT' is actually $81k USD.
Key takeaways
What you should consider as a trader
- Volume dominated by USDT pairs - Over 70% of BTC volume is BTC/USDT.
- USDT redemption isn't free - $100K minimum, identity verification required.
- Price divergence happens - BTC/USDT and BTC/USD diverge during stress.
- Your mental accounting is wrong - Track what you paid for USDT.
- The peg is an assumption - 1 USDT = 1 USD is marketing.
Data you need
Track true USD exposure
Data points:
- USDT/USD actual rate
- BTC/USD vs BTC/USDT spread
- Volume by pair
- True portfolio value
Comparison of data sources
Where to get crucial data feeds
| Source | Availability | Notes |
| CoinGecko | ⚠️ Partial | 'USD' prices are really USDT. |
| Kraken/Coinbase | ⚠️ Partial | Real USD pairs but lower liquidity. |
| **Madjik** | ✅ Yes | 🚀 Get API Access Now |
Available metrics for this hypothesis:
| Metric | Description | Change dimensions | Time dimensions | How to use | API spec |
| `ME10001` | Stablecoin peg | • Absolute Value (value) • Relative Change (relchg) • Score 0-100 (score) | • Current (now) • Past 24 Hours (past24h) • Past 7 Days (past7d) | Example | API |
| `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 |
| `ME10004` | Market valuation | • Absolute Value (value) • Relative Change (relchg) • Score 0-100 (score) | • Current (now) • Past 7 Days (past7d) • Past 30 Days (past30d) | Example | API |
Clean data for AI, A2A, MCP, etc.
Science behind hypothesis
Research supports this hypothesis
University of Texas study found USDT isn't always backed by real USD demand.
Bottom line
You can't manage what you don't measure. Tracking your real USD exposure helps you know your actual cost basis and P&L. Madjik converts USDT-denominated positions to true USD values, giving you accurate performance measurement.
Practical use
How to use this data in trading:
Combine these metrics for comprehensive analysis:
- ME10001 (Stablecoin Peg): Monitor USDT/USDC peg for arbitrage opportunities, flight-to-safety signals, and counterparty risk assessment across spot, perpetuals, ETFs, and MSTR.
- ME10003 (Volume Analysis): Filter wash trading to size positions correctly and detect genuine fiat inflows confirming trends.
- ME10004 (Market Valuation): Use MVRV and realized cap to identify cycle extremes for timing entries/exits across BTC, ETFs, and MSTR.
Detailed examples with Python code, AI agent integration (MCP/A2A), and risk analysis:
| `ME10001` | Stablecoin Peg Trading Guide | Example → |
| `ME10003` | Volume Analysis Trading Guide | Example → |
| `ME10004` | Market Valuation Trading Guide | Example → |
API Documentation: docs.madjik.io
For informational purposes only. Not financial, investment, tax, legal or other advice.