The indicators we will be discussing in this article utilize volume as an input.
Volume, which is a measure of the number of shares of a security traded over a given time period, can be viewed as a general representation of the activity and liquidity of a market.
VWAP is an intraday indicator that calculates the ratio of an asset’s average price to its volume, while VWMA is a type of moving average that can be applied at any timescale. It emphasizes the volume of trade by weighing prices according to trading activity.
Understanding how these indicators are calculated, how to interpret their output, and when to use them can potentially help traders become better at their craft.
VWAP represents the ratio of a security’s traded value to its total transaction volumes in a trading session. It creates a modified average price of a security by changing the average price based on transaction volumes that occur within particular time intervals. VWAP is exclusively applied to intraday timeframes, so the indicator is a favorite among traders who operate within shorter time horizons, such as day traders.
Accordingly, VWAP (as the name suggests) takes the average price and the traded volume weights of a security during a specific period to signal strength or weakness of price action.
Even though VWAP relies on intraday data, it is still technically considered a lagging indicator. Since the VWAP calculates an average price to volume value from the start of the opening bell, it can be used to confirm intraday trends, signaling to traders whether to take a short or long position depending on whether the metric is falling or rising, respectively.
The VWAP formula equals the sum of each dollar transaction divided by the total volume of shares traded between the market open and the latest intraday time print.
1. Calculate the Average Price from the opening bell
[(Highest Price + Lowest Price + Closing Price)/3)]
2. Multiply this Average Price with the Volume from the opening bell
(Typical Price x Volume)
3. Calculate the Aggregate Total of Average Price
Aggregate(Typical Price x Volume)
4. Find the Aggregate Total of Volume
5. Divide the Aggregates as shown in the VWAP formula
VWAP = Aggregate (Typical Price x Volume) / Aggregate (Volume)
At a basic level, the use case of VWAP is similar to the use case of a simple moving average. When prices rise above the VWAP, it potentially indicates that the security is establishing or has already established an uptrend, and when they fall below it, it may signal an imminent or continuing downtrend. Some traders view price alone as an insufficient determinant of trend and believe that an increase in volume is needed to confirm a new trend. These traders in particular are inclined to use VWAP to set rules for their trading strategies and that are based on trends.
1. Using VWAP to Set Buy Order
Experienced traders often use stop and limit orders to specify their entries ahead of time rather than using a market order that accepts the current price offered by market makers. Trading strategies based on VWAP naturally fit with this approach. For long setups, traders that practice trend following are likely to place a stop order above the VWAP, whereas mean-reversion traders may place a limit order below it.
2. Using VWAP to Set Sell Order
Similarly, professional traders approach their craft with defined exit parameters guiding their trades. VWAP can be useful in this respect because it can help a trader exit a position once a trend has changed. Mean reversion traders looking to short may want to execute a sell order above the VWAP because it means the security will be sold at a price above the average.
The VWAP is a lagging indicator, requiring a strict set of rules to use it effectively. Traders have two options when using VWAP: to focus on trends or mean reversion. For those using trends as the foundation for a trading strategy, a strong uptrend in the price of a security (above the VWAP) signals the movement may continue.
Mean reversion traders should use short periods to determine the average price of an asset and anticipate a turnaround. For example, they can set the VWAP to one to three (1-3) hours to identify a “fast” moving reversal in a security’s price. It will ensure the trader reacts fast enough to take a position before most traders take similar action.
VWAP indicates a bullish sentiment when prices are above it and bearish sentiment when prices are below it.
In a bullish market, traders can use VWAP in a pullback. For example, a security that is on an extended movement upwards makes a change in the opposite direction. Since the price is above VWAP (indicating bullish conditions), mean reversion traders can buy that security. They enter a long time and wait for the price of the asset to rise once more. Having a stop-loss level is necessary for the success of this strategy.
When markets are showing bearish sentiment, traders can use VWAP after identifying a breakout. Traders identify a security that holds a strong resistance level but starts to show a price increase accompanied by higher traded volumes. Since the level of activity in the market is still low, it signifies that the security has not gained adequate attention. Traders can take a long position, anticipating that a change in the market condition will increase interest in the security.
The Volume Weighted Moving Average (VWMA) also incorporates volume into the calculation but strictly uses the closing prices of securities. Like VWAP, this indicator also weighs the price data based on the volume activity that takes place in a period. Accordingly, the price data points that coincide with heavy trading volume receive more weight compared to those that coincide with lighter trading.
VWMA is also a considered lagging indicator, meaning that the values it prints only change after the price of the security it is tracking has itself changed. For this reason, VWMA is primarily used by trend followers to identify trends that they expect will continue over time.
The VWMA formula requires traders to identify a specific period for evaluation. Assuming three days, the VWMA formula is as shown below.
C = closing price
V = volume
The VWMA applies the idea of moving averages to both price and volume.
1. Multiply the closing prices for the chosen period by the volume of each trade
2. Divide the price moving average (above) by the volume moving average.
3. The result of the calculation gives the volume-weighted moving average (VWMA).
How traders interpret the VWMA output depends on the style of the trader, the relationship of the indicator to the price of the security, and the shape of its slope. For example, if the price sits above the VWMA and the slope of the VWMA points upwards, this pattern suggests that the security is trending higher. Trend followers would be likely to take or hold long positions.
Similarly, if the price of a security sits below the VWMA and the slope of the VWMA points downwards, it suggests the price is trending lower. Here a trend follower would take or hold a short position under these market conditions.
Usually, traders use VWMA together with other indicators, for example, a Simple Moving Average (SMA). Combining them offers traders several insights:
1. Determine the occurrence of trends
A VWMA that closely follows the SMA signals increased volume accompanied by higher buying and selling. As a result, traders can decide what position to take.
2. Confirm the existence of trends
A divergence between the VWMA from the SMA suggests strength in a trend. In this case, the VWMA enables traders to identify market trends and determine their strengths.
3. Signify a directional change
The combination of the VWMA and price (with price crossing the VWMA) can indicate a directional change in the trend. Accordingly, traders should reconsider their position in the market.
The VWMA is best suited for noisy markets filled with false signals. Traders in such markets need to separate signal from noise in order to better estimate the direction and magnitude forward returns will take. By comparing the price movement and the VWMA, traders may be able to identify a directional change when the price crosses the VWMA. They can assume long or short positions depending on their own trading style and the expected price movement.
As noted, the use of VWMA in trading research is often enhanced by combining additional indicators such as the SMA. If the price of an asset breaks through the SMA, driving the VWMA below it, the price action suggests an accelerating bearish trend. Momentum traders can start looking for a short position. On the other hand, when price rises above the VWMA, pulling it above the SMA the price action indicates bullish conditions in the market. Accordingly, momentum traders can start to look for long positions.
A momentum trader who has taken a long position and notices no separation between the VWMA and the SMA might consider exiting the market. Traders often interpret this set up as a signal that the trend has ended.
Both the volume-weighted average price (VWAP) and the volume-weighted moving average (VWMA) can be useful indicators to guide the decisions of traders.
VWAP is an intraday measure that calculates the aggregate of the average price at specific time intervals, and adjusts the number based on weighted transaction volume. The indicator includes all the data over a given period, and the calculation starts at the beginning of a trading session. VWAP helps short term traders to determine the average price of a security by factoring in transaction volumes.
VWMA is a moving average that calculates the average closing price weighted by volume. It’s primarily used outside of intraday scenarios. The indicator takes the closing prices of a security at distinct time intervals as an input period. VWMA then weighs the price of an asset based on its trading activity in a period.
And of course, it always makes sense for traders to backtest the influence of indicators like VWAP and VWMA on the forward return of securities before putting money at risk in live markets.
Start with the free version and upgrade when you need a larger metric library and longer lookback periods.