Cumulative Outperformance | viResearch

Cumulative Outperformance | viResearch

📈 Compare. Measure. Dominate.
Cumulative Outperformance | viResearch is a performance benchmarking tool designed for traders who want a deeper understanding of how their asset stacks up against a selected benchmark—such as BTC, SPX, or any TradingView-supported symbol—over time.

Built for high-level comparative analysis, this indicator plots the rolling relative performance of the asset vs. a benchmark, showing whether the asset is outperforming or underperforming in a clean, data-rich format.

🧠 Core Logic & Analytics
✔️ Rolling Returns → Tracks cumulative return over a custom period (default: 35 bars)
✔️ Benchmark Flexibility → Choose any ticker (e.g., INDEX:BTCUSD) as your benchmark
✔️ Custom Start Date → Isolate performance from a meaningful date (e.g., macro events)
✔️ Dynamic Outperformance Plot → See how much stronger or weaker your asset is

📊 Advanced Visualization
🎯 Outperformance Line → Color-coded performance differential between asset and benchmark
🎯 Zero Line Reference → Histogram-style centerline for clarity
🎯 Info Panel (Table) → Shows benchmark symbol, exact outperformance %, and status (Outperforming / Underperforming / Even)
🎯 Real-Time Labeling → Inline data label shows current performance gap directly on chart

🔔 Built-In Alert Engine
🔹 Fires alerts when your asset starts outperforming or underperforming
🔹 Uses once_per_bar_close logic to avoid intrabar noise
🔹 Ideal for monitoring passive investments or pair trading setups

👤 Ideal For:
📈 Macro analysts comparing assets post-event
⚖️ Relative strength traders or long/short pair strategists
💼 Fund managers evaluating performance attribution
🔍 Traders analyzing sector rotation or asset flows

✅ Summary
Cumulative Outperformance | viResearch is a precision benchmarking tool that enables traders to visually and quantitatively assess how an asset performs relative to another. Use it to track momentum divergence, build pair strategies, or confirm asset rotation dynamics.