Volume-Weighted Average Price (VWAP)

Volume-weighted average price (VWAP) is the average price at which a security has traded over a given period, usually one trading day, with each trade counted in proportion to its size. A trade of 10,000 shares affects the figure ten times as much as a trade of 1,000. The result is the price at which the typical share changed hands, which is why VWAP is treated as a fair summary of where the market traded.

VWAP is one of the most widely used benchmarks in equity trading. Institutional investors use it to judge how well their brokers executed an order, brokers offer algorithms designed to match it, and day traders read it as an indicator of intraday trend. It is used in the same way for futures, bonds and crypto assets. It is often compared with the time-weighted average price (TWAP), which weights each time interval equally regardless of how much traded.

The standard calculation is:

• $P_i$ is the price of trade $i$.
• $Q_i$ is the quantity traded in trade $i$.
• The sums run over all trades in the chosen period.

Suppose three trades take place in a share during a session: 1,000 shares at 10.00, 3,000 shares at 10.20 and 1,000 shares at 10.50. The value traded is 10,000 plus 30,600 plus 10,500, which is 51,100. The volume is 5,000 shares. VWAP is 51,100 divided by 5,000, or 10.22. A simple average of the three prices would be 10.23; the VWAP is lower because the largest trade took place at 10.20.

Data vendors and charting tools usually calculate VWAP cumulatively from the open, updating it with every trade or at fixed intervals using a representative price for each interval. Calculations can differ slightly depending on which trades are included, for example whether auctions, off-exchange trades and late-reported blocks are counted.

A buyer whose average purchase price is below the day's VWAP has paid less than the average market participant, and a seller above VWAP has received more. Asset managers therefore compare their fills with VWAP in transaction cost analysis and in reviewing best execution. The benchmark is easy to compute and to explain, and it does not reward a broker simply for trading quickly or slowly.

Brokers offer two main services built on it. In an agency VWAP order, an algorithm tries to match the benchmark on the client's behalf, and the client keeps any difference. In a guaranteed VWAP trade, the broker commits to fill the order at the day's VWAP, often for a fee, and bears the risk of doing worse.

A VWAP algorithm is a form of algorithmic trading that splits a large parent order into many small child orders and spreads them through the day in line with the expected pattern of market volume. Because trading in most shares is heaviest near the open and the close, a typical schedule is U-shaped. The algorithm uses historical volume profiles, adjusts to actual volume as the day unfolds and decides for each slice whether to post a passive limit order or cross the spread. Trading in step with the market in this way limits market impact and hides the size of the order. Related strategies target a fixed percentage of volume, or the closing price through the closing auction.

On intraday charts, VWAP is plotted as a line that many short-term traders treat as a reference level: a price above it is read as a sign that buyers have been in control during the session, and a price below it the opposite. Variants include anchored VWAP, which starts the calculation from a chosen event such as an earnings release, and bands drawn at set distances from the line.

VWAP also appears in legal documents. The price of shares in a share buyback programme, the conversion terms of a convertible bond, the consideration in share-based mergers and the pricing of placements are frequently set by reference to the VWAP over a stated number of days, because an average over many trades is harder to distort than a single closing price. In crypto markets, reference rates and oracles often use volume-weighted prices across several exchanges for the same reason.

As a benchmark, VWAP has well-known weaknesses. An order that makes up a large share of the day's volume largely determines the VWAP itself, so matching it says little about cost. The measure ignores the price at the moment the investment decision was made: if a share rises steadily all day, a buyer can match VWAP and still pay far more than the morning price. Implementation shortfall, which measures cost against the decision price, addresses this. A trader judged against VWAP also has an incentive to spread an order across the day even when faster or slower execution would serve the client better.

As an indicator, VWAP is backward-looking and resets each session, so it carries no information across days unless anchored. In thin markets, or where reported volume is inflated by a wash trade, a volume-weighted price can be unrepresentative. With trading split across many venues, the figure also depends on which venues are included, a consequence of liquidity fragmentation.