Ghost Feed

The Ghost Feed tool overlays a second symbol's price data onto the current chart. The overlay is normalized to the primary symbol's price scale so both series can be compared visually. The ghosted data appears as a semi-transparent, dashed line that tracks the secondary symbol's price movements in parallel with the primary. This creates a visual comparison that reveals correlation strength, relative performance, and divergences at a glance without needing any external tools.

This is a powerful tool for intermarket analysis, correlation trading, pairs trading, and identifying relative-strength divergences between related instruments. The ghost can be normalized using price-based scaling, percentage-based scaling (both at 100% for relative performance), or z-score normalization for statistical comparison. Each normalization method reveals a different aspect of the relationship between the two instruments — choose the one that matches your analytical question.

The ghost overlay is normalized to the current visible range. When you scroll or zoom, the normalization recalculates to maintain the visual comparison. This means the ghost always appears aligned with the primary symbol regardless of your current view — but it also means the ghost's absolute price values are not displayed, only its relative movement. For absolute price comparison across the full data range, use percentage normalization which preserves the relationship over time and does not recalculate as aggressively with view changes.

Ghost Feed differs from simply adding a second pane with the same data because the overlay is directly on top of the primary chart. This direct overlay makes divergences immediately obvious — you can see at a glance whether both instruments are moving in the same direction, whether one is leading the other, or whether they have decoupled entirely. The correlation display option adds a quantitative measure of the relationship strength for the visible range.

1. 1
   Select Ghost Feed

   Click the Ghost Feed tool from the annotation toolbar.
2. 2
   Choose the symbol

   Enter the ticker or symbol to overlay (e.g. "MSFT", "SPY", "BTC/USD").
3. 3
   Set normalization

   Choose how the ghost is normalized: price, percentage, or z-score.
4. 4
   Adjust visual style

   Set opacity, line color, and line style for the ghost series.
5. 5
   Review the overlay

   The ghost series appears on your chart. Scroll and zoom to see how the comparison holds across different views.
6. 6
   Enable correlation

   Turn on the correlation display to see the Pearson coefficient for the visible range.

• Correlated pairs analysis — overlay EUR/USD on USD/CHF (inverse correlation), gold on silver (strong positive), or SPX on NDX to visually confirm correlation strength and identify divergences in real time.
• Divergence identification — when the ghost series moves opposite to the primary despite a historical positive correlation, a reversion to the mean may be due. This is a common and profitable intermarket trading signal.
• Relative strength analysis — overlay a competitor's stock on the primary stock to see which is outperforming. If AAPL is rising faster than MSFT (the ghost), AAPL has relative strength. This is the foundation of sector rotation strategies.
• Cross-timeframe context — ghost the daily chart on a 4H chart for higher-timeframe context. Understanding where the daily trend is relative to intraday price helps align short-term trades with the bigger picture.
• Pairs trading — identify mean-reversion opportunities by ghosting one pair on another. When the spread widens beyond its historical range (2+ standard deviations), enter a pairs trade betting on statistical convergence.
• Sector rotation — ghost the sector ETF (e.g. XLF for financials) on an individual stock to see if the stock is leading or lagging its sector. Leaders in strong sectors are prime candidates for long positions.
• Benchmark comparison — overlay a benchmark index (SPY, QQQ, IWM) on a managed portfolio or strategy equity curve to evaluate alpha generation and relative performance over time.

Price-based normalization aligns the two series at their current price levels. This is the simplest method and works well when comparing instruments with similar price values (e.g. two stocks both trading around $150). The ghost's absolute values are preserved but shifted to match the primary's current level. Price normalization is best for short-term comparison where the absolute price relationship matters for the analytical question at hand.

Percentage normalization sets both series to 100 at the left edge of the visible range. From that point, each series shows its percentage change. This is the best method for comparing instruments with different price levels because it normalizes for price differences and shows relative performance directly — if the primary is at 105 and the ghost is at 98, the primary has outperformed by 7%. Z-score normalization standardizes both series to have a mean of 0 and standard deviation of 1, revealing statistical divergences regardless of price scale or inherent volatility.

• 1.Compare and overlay tools — TradingView Help
• 2.Technical Analysis of Financial Markets — John J. Murphy
• 3.Intermarket Technical Analysis — John J. Murphy
• 4.Pairs Trading: Quantitative Methods and Analysis — Ganapathy Vidyamurthy
• 5.The Visual Investor — John J. Murphy
• 6.Correlation Analysis in Finance — Statistical reference