The Weighted Moving Average (WMA) is another type of moving average used in stock technical analysis that assigns different weights to each data point, giving more importance to recent data compared to older data. This makes the WMA more responsive to recent price changes than the Simple Moving Average (SMA), though not as much as the Exponential Moving Average (EMA).
Calculation of WMA
The calculation of the WMA involves assigning a specific weight to each price point in the data set, with the most recent price receiving the highest weight. Here’s a step-by-step process:
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Assign weights: Assign weights to each data point, with the most recent data point having the highest weight. The weights decrease in a linear fashion for older data points.
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Multiply prices by their respective weights: Multiply each price in the data set by its assigned weight.
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Sum of weighted prices: Add up all the weighted prices.
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Sum of weights: Add up all the weights.
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Calculate WMA: Divide the sum of weighted prices by the sum of weights.
WMA=∑i=1n(Pricei×Weighti)∑i=1nWeighti\text{WMA} = \frac{\sum_{i=1}^{n} (\text{Price}_i \times \text{Weight}_i)}{\sum_{i=1}^{n} \text{Weight}_i}
Where:
- nn is the number of periods.
- Pricei\text{Price}_i is the price at period ii.
- Weighti\text{Weight}_i is the weight assigned to the price at period ii.
Example of WMA Calculation
Let's consider a 5-day WMA with the following closing prices: 50, 52, 54, 56, 58. We'll assign weights from 1 to 5, with 5 being the weight for the most recent price.
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Assign weights:
- Day 1 (oldest): 50 (weight 1)
- Day 2: 52 (weight 2)
- Day 3: 54 (weight 3)
- Day 4: 56 (weight 4)
- Day 5 (most recent): 58 (weight 5)
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Multiply prices by weights and sum:
(50×1)+(52×2)+(54×3)+(56×4)+(58×5)=50+104+162+224+290=830(50 \times 1) + (52 \times 2) + (54 \times 3) + (56 \times 4) + (58 \times 5) = 50 + 104 + 162 + 224 + 290 = 830
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Sum of weights:
1+2+3+4+5=151 + 2 + 3 + 4 + 5 = 15
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Calculate WMA:
WMA=83015=55.33\text{WMA} = \frac{830}{15} = 55.33
Advantages of WMA
- More responsive to recent data: The WMA reacts more quickly to recent price changes compared to the SMA, making it useful for identifying short-term trends.
- Weight distribution: By assigning linear weights, it provides a balance between smoothing the data and responsiveness, although it’s less reactive than the EMA.
Common Uses in Technical Analysis
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Trend Identification:
- Similar to other moving averages, if the price is above the WMA, it is generally considered an uptrend. Conversely, if the price is below the WMA, it indicates a downtrend.
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Support and Resistance Levels:
- The WMA can act as a dynamic support or resistance level, where prices may tend to bounce off the WMA line.
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Crossovers:
- Traders often use the WMA in crossover strategies with other WMAs or different types of moving averages (e.g., a 10-day WMA crossing above a 30-day WMA could signal a buy, and vice versa).
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Confirming Signals:
- The WMA can be used alongside other technical indicators to confirm trends and signals, providing additional reliability.
Comparison with Other Moving Averages
- SMA vs. WMA: The SMA gives equal weight to all data points, while the WMA gives more weight to recent prices, making the WMA more responsive to recent changes.
- EMA vs. WMA: Both the EMA and WMA give more weight to recent prices, but the EMA’s weighting decreases exponentially, making it more sensitive to recent price changes than the WMA’s linear weighting.
Conclusion
The Weighted Moving Average is a useful tool in technical analysis for traders who want to give more importance to recent price movements while still smoothing out data to identify trends. Its linear weighting approach offers a balanced sensitivity to price changes, making it a versatile option for various trading strategies.