Technical Analysis Logic

• Mathematical Validation: Run the logic against a known sample dataset (e.g., a specific stock's historic data) and compare with a trusted source (TradingView, Yahoo Finance).
• Edge Case Check:
  • How does it handle missing data points?
  • What happens during the initial "warm-up" period (e.g., the first 20 days of a 20-MA)?
  • How does it handle zero volume or zero price movement?

Ask explicitly:

“Have we verified the calculation logic against a trusted baseline for this indicator?”

4️⃣ Performance Optimization

For data-intensive calculations:

• Incremental Calculation: Calculate only the latest data point instead of re-calculating the entire history when a new tick arrives.
• Offloading: Move heavy computations to Rust/Backend if the dataset exceeds 1,000 points.
• Memoization: Ensure calculated values are cached in React (useMemo) or a dedicated state store.

5️⃣ Trading Signal Definition

When defining signals (Buy/Sell/Hold):

• Combine Multiple Indicators: Avoid single-indicator signals. Use volume confirmation or trend filtering.
• Signal States:
  • Triggered: The exact moment the condition is met.
  • In-Progress: The condition is still true after being triggered.
  • Cooling: Prevention of rapid re-triggering (debounce).

6️⃣ Implementation Workflow

Step 1: Core Function

Implement the pure mathematical function.

function calculateSMA(data: number[], period: number): number[] { ... }

Step 2: Verification

Test with dummy data.

Step 3: UI Integration

Bind to the chart or signal list.

Step 4: Verification Gate

Check precision (floating point issues) and UI lag.

7️⃣ Refusal Conditions

Refuse to proceed if:

• Data source is unreliable or lacks OHLCV.
• Indicator parameters are not defined (e.g., "just add a trend line").
• Calculation logic is "proprietary" without a mathematical explanation.

Key Principles

• Accuracy > Visuals
• Handle floating point precision carefully
• Document the "warm-up" requirements
• Prefer vectorized operations for speed