Volume weighted average price (VWAP)

Calculate the cumulative Volume Weighted Average Price (VWAP) for intraday trading analysis. VWAP is a trading benchmark that represents the average price at which an asset has traded throughout the day, weighted by volume. It's widely used by institutional traders to assess execution quality and identify trend strength.

Problem: Calculate running VWAP​

You want to calculate the cumulative VWAP for a trading day, where each point shows the average price weighted by volume from market open until that moment. This helps traders determine if current prices are above or below the day's volume-weighted average.

Solution: Use typical price from OHLC data​

The industry standard for VWAP uses the typical price formula from OHLC (Open, High, Low, Close) candles:

Typical Price = (High + Low + Close) / 3
VWAP = Σ(Typical Price × Volume) / Σ(Volume)

This approximation is used because most trading platforms work with OHLC data rather than tick-level trades. We use the fx_trades_ohlc_1m materialized view which provides 1-minute candles:

Calculate cumulative VWAPDemo this query
WITH sampled AS (
  SELECT
    timestamp, symbol,
    total_volume,
    ((high + low + close) / 3) * total_volume AS traded_value
  FROM fx_trades_ohlc_1m
  WHERE timestamp IN yesterday() AND symbol = 'EURUSD'
),
cumulative AS (
  SELECT
    timestamp, symbol,
    SUM(traded_value) OVER (ORDER BY timestamp) AS cumulative_value,
    SUM(total_volume) OVER (ORDER BY timestamp) AS cumulative_volume
  FROM sampled
)
SELECT timestamp, symbol, cumulative_value / cumulative_volume AS vwap
FROM cumulative;

This query:

  1. Reads 1-minute OHLC candles and calculates typical price × volume for each candle
  2. Uses window functions to compute running totals of both traded value and volume
  3. Divides cumulative traded value by cumulative volume to get VWAP at each timestamp

How it works​

The key insight is using SUM(...) OVER (ORDER BY timestamp) to create running totals:

  • cumulative_value: Running sum of (typical price × volume) from market open
  • cumulative_volume: Running sum of volume from market open
  • Final VWAP: Dividing these cumulative values gives the volume-weighted average at each point

When using SUM() OVER (ORDER BY timestamp) without specifying a frame clause, QuestDB defaults to summing from the first row to the current row, which is exactly what we need for cumulative VWAP.

Multiple symbols​

To calculate VWAP for multiple symbols simultaneously, add PARTITION BY symbol to the window functions:

VWAP for multiple symbolsDemo this query
WITH sampled AS (
  SELECT
    timestamp, symbol,
    total_volume,
    ((high + low + close) / 3) * total_volume AS traded_value
  FROM fx_trades_ohlc_1m
  WHERE timestamp IN yesterday()
    AND symbol IN ('EURUSD', 'GBPUSD', 'USDJPY')
),
cumulative AS (
  SELECT
    timestamp, symbol,
    SUM(traded_value) OVER (PARTITION BY symbol ORDER BY timestamp) AS cumulative_value,
    SUM(total_volume) OVER (PARTITION BY symbol ORDER BY timestamp) AS cumulative_volume
  FROM sampled
)
SELECT timestamp, symbol, cumulative_value / cumulative_volume AS vwap
FROM cumulative;

The PARTITION BY symbol ensures each symbol's VWAP is calculated independently, resetting the cumulative sums for each symbol.

Different time ranges​

-- Current trading day
WHERE timestamp IN today()

-- Specific date
WHERE timestamp IN '2026-01-12'

-- Last hour
WHERE timestamp >= dateadd('h', -1, now())
Trading use cases
  • Execution quality: Institutional traders compare their execution prices against VWAP to assess trade quality
  • Trend identification: Price consistently above VWAP suggests bullish momentum; below suggests bearish
  • Support/resistance: VWAP often acts as dynamic support or resistance during the trading day
  • Mean reversion: Traders use deviations from VWAP to identify potential reversal points
Related documentation