Skip to main content
Track Volume-weighted average price
1 / 18
Library

2000issue C121-5

Volume-weighted average price as a baseline for indicator construction

A last print can sit far from the prices that carried most of the session. A band model reads differently when its center is a volume-weighted average rather than a closing price.

  • A volume-weighted average is built from many trades, so larger executions receive more weight than smaller ones.
  • A closing price can sit outside the range that carried most of the day's volume and can misrepresent the session that actually traded.
  • Bollinger Bands can be rebuilt on a volume-weighted average line, using an explicit lookback and a stated deviation multiple.
  • Historical volume-weighted averages may have to be computed from the tape, so the filter is only as complete as the trade-level input.
Entries in this reading2 entries

A close can miss the session that traded

A closing price is the last reported transaction of a bar. That print can sit far from the prices that carried most of the day's volume.

When the last trade sits well outside the range that carried most of the day's volume, a close-based input can misrepresent the session that actually traded. That is marking the close: an end-of-session print outside the day's main traded range that can distort close-based calculations.

How the volume-weighted average is built

A volume-weighted average is constructed from many trades rather than from one arbitrary print. Each print is weighted by its traded size, so larger executions receive more weight than smaller ones.

Some venues replace the final print with a short-window volume-weighted average when setting the official close. They treat that average as the executable end-of-day reference.

Rebuilding a band on the volume-weighted line

Bollinger Bands are an envelope built from a moving central value plus and minus a multiple of the same series' standard deviation. The envelope can be rebuilt on a volume-weighted average line instead of closing prices, using an explicit lookback and a stated deviation multiple.

Side-by-side charts of the same name can look different when one series is the close and the other is the volume-weighted average. That difference changes how a band model is read.

The filter is only as complete as the tape

Historical volume-weighted averages are not always stored by a data vendor. They may have to be computed from the tape. The filter is only as complete as the trade-level input.

Companion fields in a quote recap

A quote-recap construction can report the volume-weighted average together with spread-to-price, trade-size, and standard-deviation fields. The same interval then also describes cost and dispersion.

Spread-to-price is the quoted spread scaled by price. It is used here as a microstructure companion to the volume-weighted average.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
1 of 18 in the Volume-weighted average price track
20011-5 pp.Next on Volume-weighted average priceConstructing VWAP support and resistance from cumulative volumeA session volume-weighted average price is the size-weighted mean of traded prices. A daily approximation multiplies each day's midpoint price by volume and divides the change in that product by the change in cumulative volume.
All readings on this track · 18 readings
  1. 2000Volume-weighted average price as a baseline for indicator construction
  2. 2001Constructing VWAP support and resistance from cumulative volume
  3. 2001An elastic volume-weighted moving average from a share-count lookback
  4. 2001Constructing an elastic volume-weighted average and volatility bands
  5. 2004Volume-weighted column averages and crossovers on point-and-figure charts
  6. 2004Session volume-weighted average for limit placement and listed routing
  7. 2008Building MIDAS curves from an anchored volume-weighted average
  8. 2008Construct a launch-point VWAP as support and resistance filters
  9. 2014Workstation order routing, VWAP, and session filters
  10. 2015Constructing price gravity and float turnover filters
  11. 2015Constructing four-stage cycles with anchored VWAP
  12. 2017Constructing a volume-weighted crossover and breakout as one swing rule set
  13. 2017Constructing a volume-weighted moving-average crossover
  14. 2017Constructing anchored volume-weighted average price maps for crowd-visible execution costs
  15. 2018Order book heatmaps, VWAP, and flow for execution
  16. 2018Constructing futures rolls ahead of first notice day
  17. 2019Evaluate a mechanical futures system as one procedure
  18. 2020Every bounce is a falsifiable regime test
All 19 readings tagged Volume-weighted average price
Also on Volume-weighted average price5 readings