BTC Dominance
Tracks BTC market cap dominance from CoinGecko. Falling dominance (rotation into alts) flips this scanner long-bias on alts. Rising dominance (capital concentration in BTC) flips short-bias on alts. Uses 7-day rate of change to filter intraday noise.
What is this scanner?
Tracks BTC market cap dominance from CoinGecko. Falling dominance (rotation into alts) flips this scanner long-bias on alts. Rising dominance (capital concentration in BTC) flips short-bias on alts. Uses 7-day rate of change to filter intraday noise.
The BTC Dominance scanner operates across 1d timeframes and refreshes every 300 seconds, ensuring you see fresh signals as conditions develop.
Origin & History
Regime detection has its roots in Hamilton's Markov Switching Models (1989) and has become central to adaptive strategy allocation in quantitative finance.
The QSA implementation of BTC Dominance builds on this foundation with quantitative thresholds calibrated specifically for crypto perpetual futures markets. The 24/7 nature of crypto trading and the unique dynamics of DEX markets like Hyperliquid require different parameters than traditional market approaches.
Detection Criteria
Btc dominance Analysis
Evaluates btc_dominance data to identify qualifying patterns and confirm signal validity.
Rate of change Analysis
Evaluates rate_of_change data to identify qualifying patterns and confirm signal validity.
Multi-Timeframe Validation
Cross-references the signal across multiple timeframes to ensure alignment and reduce false positives.
Volume Confirmation
Requires volume to be above the 20-period average to confirm institutional participation in the move.
Grading Breakdown
Textbook btc dominance signal with 4+ domain categories confirming, rare category multipliers contributing, and strong regime alignment. These represent the top 1-2% of signals.
Strong btc dominance signal with 3+ categories confirming. Good domain diversity and meaningful rarity bonuses from contributing scanners.
Valid btc dominance detection with 2-3 confirming categories. The core pattern is present but lacks the depth of confirmation needed for higher grades.
Single-category btc dominance signal or one with limited domain diversity. Pattern detected but conviction is low — worth monitoring, not acting on alone.
Common Mistakes
Treating regime signals as direct trade triggers. Regime is context, not a setup — use it to filter other scanners.
Not adjusting strategy allocation when regime changes. Running momentum strategies during CHAOS is a recipe for losses.
Ignoring regime transitions. The shift from QUIET to NORMAL is often the most profitable period to be positioned.
Over-trading during CHAOS because volatility looks exciting. High volatility ≠ high probability.
How to Trade
Entry Context
Use regime context to filter other scanners. In QUIET regimes, prioritize breakout scanners. In NORMAL, all strategies are viable. In CHAOS, reduce size or wait.
Risk Management
Adjust position sizes by regime state. QUIET: normal size. NORMAL: normal to slightly larger. CHAOS: 50% size or sit out. This single rule dramatically improves risk-adjusted returns.
Target Framework
Target expectations vary by regime. QUIET-to-NORMAL transitions produce the largest moves. NORMAL trends are steady and predictable. CHAOS is binary — take profits quickly if profitable.
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QuantScan AI scans 200+ crypto perpetuals in real-time, 24/7. Not financial advice. Past performance does not guarantee future results.