VWAP (Volume Weighted Average Price)

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    Education, Technical Indicators
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Hakan Kwai
Instructor

VWAP stands for Volume-Weighted Average Price. It is a trading indicator that represents the average price of a financial instrument over a specific period, weighted by the trading volume.

 

VWAP is commonly used by institutional investors and traders, especially those involved in algorithmic trading. It is considered a benchmark for assessing the execution quality of trades and determining whether a trader’s execution price is better or worse than the average market price.

 

The calculation of VWAP involves taking the sum of the product of each trade’s price and volume and dividing it by the total trading volume over a given period. This weighted average price is then plotted on a chart to provide a visual representation of the average price at which a financial instrument has traded.

 

VWAP is often used in conjunction with intraday charts to compare the current price of a financial instrument to its average traded price. Traders use VWAP as a reference point to determine whether the current price is above or below the average, which can help identify potential buying or selling opportunities.

 

Additionally, VWAP is used for assessing the performance of trading algorithms, particularly those designed to execute trades at or near the VWAP price. By comparing the executed price to the VWAP, traders can evaluate the effectiveness of their algorithmic trading strategies.

 

VWAP is also used by institutional traders to minimize market impact when executing large orders. By executing trades close to the VWAP, traders aim to reduce the impact of their trades on the market and avoid significantly moving the price against their desired direction.

 

In summary, VWAP is a trading indicator that represents the average price of a financial instrument over a specific period, weighted by the trading volume. It is used as a benchmark for evaluating trade execution quality, identifying potential trading opportunities, assessing algorithmic trading performance, and minimizing market impact for large orders.

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