Calculate Volume Weighted Average (VWAP)
A professional financial calculator for traders and analysts
Welcome to the definitive tool to calculate volume weighted average (VWAP). This metric is essential for institutional traders, technical analysts, and investors looking to determine the true average price of a security by accounting for the volume traded at each price level. Unlike a simple average, the volume weighted average gives more weight to prices with higher volume, providing a more accurate reflection of market sentiment.
VWAP Calculator
Enter your trade executions below. Add as many rows as needed.
Formula: Total Traded Value ÷ Total Volume
Figure 1: Visualization of Trade Volumes vs. Execution Prices.
| Trade # | Price ($) | Volume | Traded Value ($) | % of Total Volume |
|---|
What is Calculate Volume Weighted Average (VWAP)?
To calculate volume weighted average price, commonly known as VWAP, is to perform one of the most critical calculations in modern trading. It is a trading benchmark used by traders that gives the average price a security has traded at throughout the day, based on both volume and price.
Unlike a simple moving average, which treats every closing price equally regardless of how many shares were traded, VWAP emphasizes high-volume trades. This makes it an essential tool for institutional investors who need to execute large orders without disturbing the market price. When you calculate volume weighted average, you get a single number that represents the fair value of the asset for that trading session.
If you buy below the VWAP, you have achieved a better-than-average entry price relative to other market participants. Conversely, buying above the VWAP suggests you paid a premium. This is why learning how to calculate volume weighted average is fundamental for algorithmic trading strategies and execution performance measurement.
Calculate Volume Weighted Average: Formula and Explanation
The mathematics behind the request to calculate volume weighted average is straightforward but powerful. It is a cumulative calculation typically reset at the beginning of each trading day.
VWAP = (Σ (Price × Volume)) / (Σ Volume)
Here is the step-by-step logic to calculate volume weighted average:
- Calculate Typical Price: For each trade (or time bar), note the price. In more complex charts, this might be the average of High, Low, and Close prices ((H+L+C)/3), but for individual trade execution, it is the execution price.
- Calculate Traded Value: Multiply the price by the volume of shares traded in that instance. This gives you the total dollar flow for that specific trade.
- Sum the Values: Keep a running total of these Traded Values (Price × Volume).
- Sum the Volumes: Keep a running total of the Volume (shares) only.
- Divide: Divide the Cumulative Traded Value by the Cumulative Volume.
| Variable | Meaning | Unit | Typical Range |
|---|---|---|---|
| Price (P) | Execution price of the asset | Currency ($) | 0.01 – 100,000+ |
| Volume (V) | Number of units traded | Shares/Contracts | 1 – 10,000,000+ |
| Traded Value (PV) | Total money exchanged (P × V) | Currency ($) | Variable |
| VWAP | The resulting weighted average | Currency ($) | Close to current price |
Practical Examples (Real-World Use Cases)
To fully understand how to calculate volume weighted average, let's look at two distinct scenarios.
Example 1: The "Whale" Accumulation
Imagine a trader buying a stock in three distinct batches:
- Trade 1: 100 shares at $50.00 (Small purchase)
- Trade 2: 100 shares at $52.00 (Small purchase)
- Trade 3: 10,000 shares at $55.00 (Huge institutional buy)
Simple Average Calculation: ($50 + $52 + $55) / 3 = $52.33.
Calculate Volume Weighted Average:
- Value 1: 100 × $50 = $5,000
- Value 2: 100 × $52 = $5,200
- Value 3: 10,000 × $55 = $550,000
- Total Value = $560,200
- Total Volume = 10,200 shares
- VWAP = $560,200 / 10,200 = $54.92
Interpretation: The simple average ($52.33) is misleading because it ignores the massive volume traded at $55. The VWAP ($54.92) is much closer to $55, reflecting the true average cost of the position.
Example 2: Intraday Scalping
A day trader executes rapid trades on a volatile crypto asset. To assess their performance, they calculate volume weighted average of their entries to ensure they aren't chasing the pump.
- Buy 500 at $10.00
- Buy 500 at $10.10
- Buy 2,000 at $10.20
Total Value = $5,000 + $5,050 + $20,400 = $30,450. Total Volume = 3,000.
VWAP = $10.15. If the current price drops to $10.12, the trader knows their aggregate position is slightly underwater, even though they bought some shares at $10.00.
How to Use This Calculator to Calculate Volume Weighted Average
This tool simplifies the process. Follow these steps:
- Enter Data: Input the Price and Volume for your first trade execution in Row 1.
- Add Rows: If you have multiple execution levels, click "Add Trade Row" to input more data points.
- Observe Real-Time Results: As you type, the tool will automatically calculate volume weighted average and update the primary result box.
- Analyze the Chart: The chart visualizes the relationship between the price levels and the volume. Look for tall bars; these exert the most "gravity" on the VWAP.
- Review the Table: The breakdown table shows the "Weight" of each trade. This helps you identify which specific execution skewed your average the most.
Key Factors That Affect VWAP Results
When you calculate volume weighted average, several market factors influence the final metric:
- Liquidity: In low-liquidity stocks, a single large order can drastically shift the VWAP, whereas highly liquid assets (like Apple or SPY) require immense volume to move the needle.
- Time of Day: Trading volume typically spikes at the market open and close. Trades executed during these "heavy" times will dominate the calculation when you calculate volume weighted average for the full day.
- Market Trend: In a strong uptrend, the VWAP will lag slightly behind the current price (similar to a moving average). In a choppy market, price often oscillates around the VWAP.
- Order Size: As seen in Example 1, outlier order sizes render simple averages useless. The larger the order relative to the total, the closer the VWAP pulls toward that order's price.
- Execution Fees: While standard VWAP does not include commissions, net-VWAP calculations (used by some proprietary desks) might subtract fees from the price, lowering the effective average.
- Block Trades: Often, dark pool block trades are reported late or in bulk. When these hit the tape, they can cause a sudden "jump" in the VWAP calculation, surprising retail traders.
Frequently Asked Questions (FAQ)
SMA treats all data points equally. VWAP weighs them by volume. Since price moves on volume, VWAP is a truer reflection of the "center of gravity" of the market participants' money.
Yes. The math to calculate volume weighted average is universal. As long as you have a Price and a Volume (size) for the transaction, the formula works perfectly for Bitcoin, Gold, or Euro futures.
Generally, if the current price is above the VWAP, the intraday trend is considered bullish. Buyers are in control and the average participant is in profit. If below, the trend is bearish.
It is technically a lagging indicator because it is based on past data (accumulated volume and price). However, many traders use it as a dynamic support/resistance level, giving it predictive utility.
Yes, standard Intraday VWAP resets at the market open. Anchored VWAP allows you to calculate volume weighted average starting from a specific date or event, like an earnings report.
Institutional algorithms use it to break up large orders to avoid market impact. They aim to execute their buy orders at or below the VWAP to ensure they aren't overpaying compared to the market average.
You can add as many rows as needed. For extremely large datasets, traders usually use Excel or coding scripts, but for quick analysis of 5-20 trades, this web tool is ideal.
Yes. Instead of "trades," enter the purchase price and number of shares for each holding in your portfolio. The result will be the average entry price of your entire position.
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