VWAP Analysis System Development
VWAP (Volume-Weighted Average Price) — volume-weighted average price. This is one of the most important institutional benchmarks: large players assess trade execution quality relative to VWAP. VWAP analysis system helps trader understand institutional fair value and trade in context of large players.
VWAP Calculation and Standard Deviations
Basic VWAP resets each trading session (for crypto — at 00:00 UTC):
VWAP = Σ(Typical Price × Volume) / Σ(Volume)
Typical Price = (High + Low + Close) / 3
Standard Deviation Bands (VWAP Bands):
SD = sqrt(Σ(Volume × (Typical Price - VWAP)²) / Σ(Volume))
Upper/Lower Band 1 = VWAP ± 1 × SD
Upper/Lower Band 2 = VWAP ± 2 × SD
±1 SD bands cover ~68% of trading activity. Price beyond ±2 SD — statistically "extreme" and inclined to return to VWAP.
Anchored VWAP
Difference from standard: calculation starts from specific event, not session start.
Types of anchor points:
- Trend start (significant swing low/high)
- Major price break
- ATH or ATL
- Exchange listing date
- Major news event
Anchored VWAP particularly valuable for long-term analysis: VWAP from BTC's 2021 ATH (~$69k) served as resistance and support for long time.
VWAP as Dynamic Support/Resistance
Institutional logic: algo-traders of large funds execute orders relative to VWAP. Purchases below VWAP — favorable execution for long. Sales above VWAP — favorable for short. This creates self-confirming pressure on VWAP level.
Trading patterns:
- Price broke VWAP from below upward with volume → bullish signal
- Price rebounded from VWAP from above downward → bearish signal
- Price at ±2 SD → mean reversion zone
Weekly and Monthly VWAP
WVWAP (weekly) — does not reset daily. Key level for swing traders. If price holds above WVWAP — weekly structure is bullish.
MVWAP (monthly) — long-term institutional level. Position traders use MVWAP to determine overall market direction.
System displays Session VWAP, Weekly VWAP, Monthly VWAP and Anchored VWAP (multiple simultaneously) with standard deviation bands. All calculations in real-time, Python + PostgreSQL/ClickHouse for storing aggregated data, React + TradingView for visualization.