RRG Smart Money Rotation

📚 Methodology & Disclosures

The Forecortex Sector Rotation Model is a quantitative tool designed to track the relative strength and momentum of various GICS (Global Industry Classification Standard) sectors and sub-industries. Using the Relative Rotation Graph (RRG) framework, it maps industries into four key quadrants: Leading, Improving, Weakening, and Lagging. This allows investors to visualize how institutional capital ("Smart Money") rotates across the market.

1. Pure Equal-Weight Model

Unlike traditional market-cap-weighted indices where a small handful of mega-cap stocks dominate a sector's trajectory (e.g., Apple and Microsoft in XLK), this model reflects the equal-weighted performance of each industry. This provides a truer representation of the broad-based participation within each sector or sub-industry.

2. Price Synthesis & ETF Selection

To construct a pure equal-weight baseline:

• Equal-Weight ETFs: The engine prioritizes using existing, tradeable equal-weighted ETFs (such as RSPF or RSPU) where available.
• Cap-Weighted ETFs: For industries only represented by market-cap-weighted ETFs, the engine synthesizes an equal-weight price index. It does this by taking the top 10 constituent holdings of the ETF, calculating their daily percentage returns, averaging them across all holdings equally, and compounding these daily averages over time from a starting base value of 100.

3. Standardized Benchmark (RSP)

All sector and industry rotation paths are plotted relative to the Invesco S&P 500 Equal Weight ETF (RSP). Using RSP instead of the standard cap-weighted S&P 500 Index (SPY) maintains mathematical consistency with the equal-weighted inputs, isolating sector strength relative to the average stock in the market rather than mega-cap weightings.

4. Decoupled Volume Metrics

While rotation paths (RRG metrics) are calculated using equal-weighted synthetic prices, volume metrics—namely On-Balance Volume (OBV) Slope and Chaikin Money Flow (CMF)—are calculated using the actual, tradeable ETF's native volume and price data. This preserves the genuine capital flow signals and institutional liquidity trends occurring within the tradeable vehicle itself.

5. Historical Lookback

Calculations are performed utilizing daily End-of-Day (EOD) historical data covering the last 252 trading days (representing approximately one year of market history).

⚠️ Important Cautions & Disclaimers

The public must exercise caution when utilizing this tool. While it is designed to aid in spotting macro capital shifts, users should remain aware of the following structural limitations:

• Representation Risk (False Negatives): Because the synthetic price indices and ETF constituent baskets only include a subset of stocks within each industry, the model may fail to capture rotation movements if the actual stocks targeted by market participants are not included in the calculations. This can result in false-negative signals.
• Sub-Industry Coverage: The GICS mapping covers a significant portion of active sectors, and most omitted industries are typically considered uninvestable or highly illiquid for institutional size. However, there is always a chance that a sub-industry left out of the GICS mapping becomes the destination of market rotation, which will not be represented in the chart.
• Supporting Tool Only: This dashboard is provided strictly for educational and informational purposes. It should be used as a supporting analytical tool in conjunction with other macroeconomic indicators, technical analysis, and fundamental research. It does not constitute financial or investment advice.