Open Standard for Macro Consensus Divergence Analysis

This repository contains the open-source methodology, JSON schemas, and reference implementations for the consensus divergence indices used by AhaSignals.com.

We believe financial transparency is paramount. By open-sourcing our scoring logic, we allow institutional researchers and quantitative analysts to verify the integrity of our fragility signals.

📊 Methodology & Live Trackers

1. Gold Fragility Index (GFI)

The GFI quantifies the risk of a consensus reversal in the gold market by synthesizing analyst dispersion, momentum, and positioning.

• Methodology: Read the math
• Live Data: View Gold Forecast Tracker 🟢

2. Silver Structural Tension Index (SSTI)

Measures the identity crisis between silver's industrial and monetary roles.

• Methodology: Read the math
• Live Data: View Silver Forecast Tracker 🟢

3. Fed Rate Fragility Index (FRFI)

Tracks the divergence between CME FedWatch futures and prediction markets (Kalshi/Polymarket).

• Methodology: Read the math
• Live Data: View Fed Rate Fragility Index 🟢

4. US Dollar Index Forecast (DCDI)

Tracks the divergence between Wall Street currency forecasts and real-time interest rate differentials.

• Methodology: See Implied DXY calculation
• Live Data: View DXY Forecast Tracker 🟢

  Core signal: Measures the gap between EUR/USD analyst targets and the US-German yield spread.

5. S&P 500 Concentration Risk (ACRI)

Quantifies the crowding risk of the "Magnificent 7" stocks versus the broader market.

• Methodology: Read concentration metrics
• Live Data: View S&P 500 Concentration Risk 🟢

  Core signal: Tracks Top 10 weighting vs historical means and earnings contribution gaps.

6. US Treasury Yield Fragility (BMFI)

Monitoring stress in the bond market through survey divergence and positioning crowding.

• Methodology: Bond market fragility logic
• Live Data: View 10Y Treasury Yield Tracker 🟢

  Core signal: Combines SPF forecast errors with CFTC hedge fund net-short positioning extremes.

7. Bitcoin Prediction Gap (BSPG)

Measuring the sentiment disconnect between institutional ETF flows and retail prediction markets.

• Methodology: Bitcoin sentiment analysis
• Live Data: View Bitcoin Prediction Tracker 🟢

  Core signal: Detects when ETF inflows (Smart Money) diverge from Polymarket odds (Speculative Sentiment).

🛠️ Data Schemas

To ensure data integrity, all snapshots adhere to strict JSON Schemas.

📜 License

This methodology is open source under the MIT License. Data snapshots provided via AhaSignals.com are subject to their respective terms.