Weighted Moving Average: A Comprehensive Guide

With over 70% global equity trades now driven by algorithms, precision in market analysis has never been more important. Among the many tools traders rely on, the weighted moving average (WMA) stands out for giving more value to recent price data. It helps traders and analysts interpret price behaviour with greater accuracy than a simple average. This blog takes a closer look at how the WMA works, its formula, and why it remains a preferable choice in both short-term and algorithmic trading strategies.

What is the Weighted Moving Average? 

The weighted moving average (WMA) is a technical analysis tool used to smooth out price data to see the direction of a trend. This is a moving average  designed to find the average price within a defined duration. Unlike the Simple Moving Average (SMA), which treats all data points equally, the WMA prioritises recent prices more heavily. The idea is that more recent prices are more relevant than older prices. This weighting makes the WMA react more quickly to new price changes.

How to Calculate WMA 

The calculation for a weighted moving average involves a few steps that give more importance to recent data. Here is a general way to calculate it:

1. Choose a period: First, decide on the number of periods to include in the average (e.g., 10 days).
2. Assign weights: Assign a weight to each period. More recent data receives stronger weighting, while older entries hold progressively less value. For a 10-day period, the most recent day (Day 10) would have a weight of 10, the day before (Day 9) a weight of 9, and so on, down to the first day (Day 1) having a weight of 1.
3. Sum the weights: Add all the weights together to get a denominator. For a 10-day period, this would be: 10 + 9 + 8 + 7 + 6 + 5 + 4 + 3 + 2 + 1 = 55.
4. Multiply price by weight: For each day, multiply the price (like the closing price) by its assigned weight.
5. Sum the weighted values: Add all the results from step 4 together.
6. Divide: Divide the total from step 5 (the sum of weighted values) by the total from step 3 (the sum of the weights).

The general formula is:

WMA = (Price1 * Weight1 + Price2 * Weight2 + … + PriceN * WeightN) / (Weight1 + Weight2 + … + WeightN)

Where ‘N’ is the most recent period with the highest weight. Because of this process, the most recent prices have a much larger impact on the final average.

WMA vs. SMA: Key Differences

Both WMA and SMA aim to smooth price data, but they differ in how they treat recent prices. The core differences are shown below:

Feature	Weighted moving average (WMA)	Simple moving average  (SMA)
Meaning	A type of moving average that assigns more value to recent price activity for a more updated reflection of market behavior.	A moving average that gives equal importance to all prices within the selected period, providing a more general view of price direction.
Weighting	Assigns more weight to recent data.	Assigns equal weight to all data.
Responsiveness	High. Reacts quickly to price changes.	Low. Reacts slowly to price changes.
Lag	Less lag.	More lag.
Smoothness	Less smooth; follows price more closely.	Smoother line; filters out more noise.
Signals	Provides earlier signals.	Provides later, more confirmed signals.
Signal Type	Can produce more false signals.	Can produce fewer false signals.

Applications of WMA in Trading 

Traders use the WMA in several configurations to interpret different market trends. Common applications include the following:

• Identifying trend direction: This is the most common use. When the WMA line is angled up, it suggests an upward trend (a “bullish” market). When the WMA line is angled down, it suggests a downward trend (a “bearish” market). A flat or sideways WMA can indicate a non-trending or “choppy” market.
• Dynamic support and resistance: The WMA line itself can act as a changing level of support or resistance.  When markets climb, a retracement to the WMA line can occur before the next rise. In a downtrend, prices may rally up to the WMA line and “fail” before moving lower.
• Generating trade signals: Some strategies use price crossovers for signals. For example, a signal to buy might occur when the price moves from below the WMA to above it. A signal to sell might occur when the price crosses from above the WMA to below it.
• Crossover signals: Another method involves using two WMAs with different time periods (e.g., a fast 10-period WMA and a slow 50-period WMA). When the short-term WMA rises above the long-term WMA, it often triggers a buying indication. On the other hand, when the WMA moves beneath the slower WMA, it can suggest a selling opportunity.

Advantages of Using WMA 

The WMA offers several benefits due to its specific calculation method. These advantages include:

1. Increased responsiveness

The primary advantage of the WMA is its speed. Because it places more importance on the most recent prices, it reflects new market information and changes in sentiment more quickly than an SMA. This speed can help an analyst spot potential trend changes earlier than with a slower-moving average, which might still be heavily influenced by data from weeks ago.

2. Reduced lag

All moving averages have some “lag” because they are based on past data. However, the WMA has significantly less lag than an SMA. It stays closer to the current price, providing a more up-to-date look at the trend. This reduction in lag is crucial for strategies that require timely signals, as the WMA more closely follows the most recent price action rather than being “dragged down” by outdated prices.

3. Emphasis on recent data

The logic of the WMA is that recent price action is more relevant to the current market than older price action. By focusing on the newest data and minimising the impact of old prices, the WMA may give a more relevant picture of the market’s current state. It assumes the most recent trading activity better reflects the current value.

4. Clearer signal in strong trends 

During a strong, sustained trend (either up or down), the WMA will track the price very closely. This provides a clear, dynamic line of support (in an uptrend) or resistance (in a downtrend), reinforcing the strength of the current trend for the analyst.

Limitations of WMA 

While the weighted moving average has clear advantages, it also has drawbacks that are important to understand. These include:

• Sensitivity to “noise”: The WMA’s greatest strength, its responsiveness, is also a weakness. Because it reacts so quickly to price changes, it can be “fooled” by short-term price spikes or market “noise” that are not part of the real trend. This can lead to “false signals” or “whipsaws,” where the indicator suggests a trend change that does not actually happen.  
• Still a lagging indicator: Like all moving averages, the WMA is a lagging indicator. It is calculated using past prices and can only confirm a trend after it has already started. It does not predict future prices. While it has less lag than an SMA, the lag still exists. This means it may be too late to act on a signal in a fast-moving market.  
• Ineffective in volatile markets: In markets that are moving sideways (non-trending) or are extremely volatile, the WMA can produce many false signals. Its sensitivity causes it to react to random price swings, making it difficult to distinguish true trends from short-term noise.  
• Arbitrary weighting: The linear weighting system (e.g., 5, 4, 3, 2, 1) is a set rule. This specific method of assigning importance may not always be the most effective one for every market or situation.

Interpreting WMA in Market Analysis 

When analysing a market, the WMA provides context that helps an analyst understand price behavior. The core interpretations include the following:

1. Gauging trend momentum

The slope of the WMA line is a primary focus. A steeply angled WMA suggests strong momentum in the direction of the trend. If the WMA line begins to flatten out, it can be interpreted as a sign that the current trend is losing strength, even if the price has not yet reversed.

2. Assessing price extension

Analysts often observe the distance between the current price and the WMA line. When the price moves very far away from its WMA (e.g., a sharp rally that pulls price far above a rising WMA), it may be interpreted as “overextended.” This condition might suggest the price is due for a pause or a pullback toward the average.

3. Filtering market bias

The WMA can be used as a general filter to confirm the market’s bias. For example, an analyst might only consider bullish (upward) price movements to be significant if the price is already trading above the WMA. This uses the WMA as a simple confirmation tool for the prevailing trend.

Practical Example: Calculating WMA in Excel  

Let’s walk through a clear example of calculating a 5-day WMA for a stock’s closing price. Suppose we have the following 7 days of closing price data for ABC Ltd.:

• Day 1: ₹150
• Day 2: ₹152
• Day 3: ₹151
• Day 4: ₹153
• Day 5: ₹155
• Day 6: ₹156
• Day 7: ₹158

We want to calculate the 5-day WMA. This means our period is 5. We will assign weights from 1 to 5, giving the most recent day (Day 5) the highest weight.

• Weights: {1, 2, 3, 4, 5}
• Sum of Weights: 1 + 2 + 3 + 4 + 5 = 15. This is our denominator.

Step 1: Enter your data in excel sheet

First, open a blank sheet and enter your data. Put ‘Day’ in cell A1, ‘Price’ in B1, and ‘5-Day WMA’ in C1. Then, fill in the data.

A	B	C
Day	Price	5-Day WMA
1	₹150
2	₹152
3	₹151
4	₹153
5	₹155
6	₹156
7	₹158

Step 2: Type in the first WMA formula

We can’t calculate our first WMA until we have 5 days of data. So, our first calculation will go in cell C6.

• Click on cell C6.
• In the formula bar, type the following formula:
  =SUMPRODUCT(B2:B6, {1;2;3;4;5}) / 15

How this formula works:

• SUMPRODUCT(B2:B6, {1;2;3;4;5}) multiplies the corresponding items in the two ranges.
  • (B2 * 1) + (B3 * 2) + (B4 * 3) + (B5 * 4) + (B6 * 5)
  • (₹1501) + (₹1522) + (₹1513) + (₹1534) + (₹155*5) = 2294

/ 15 divides that total by the sum of the weights.

Result: 2294 / 15 = 152.933…

Important note: You must use semicolons (;) inside the {1;2;3;4;5} for Google Sheets or some versions of Excel. If you use commas (,) and get a #VALUE! error, the semicolons will fix it.

Step 3: Fill the formula down 

Now that you have the first value, you don’t need to type the formula again.

• Return to cell C6.
• Then drag the small square at the corner (fill handle) downward
• Click and drag the handle down to cell C8.
  

Excel auto-fills the formula across cells and modifies the ranges as required.

• The formula in C7 will be: =SUMPRODUCT(B3:B7, {1;2;3;4;5}) / 15
• The formula in C8 will be: =SUMPRODUCT(B4:B8, {1;2;3;4;5}) / 15
  

Step 4: Check your final results 

Your sheet is now complete and will show all the WMA values which will appear something like:

Conclusion

The weighted moving average is a technical analysis tool that prioritises recent price data to offer a responsive view of market movement. Its weighting method distinguishes it from simple averages. Analysts often observe this indicator in conjunction with other data, noting that its resulting line varies based on the time period chosen for the calculation.

FAQ‘s