Weighted Moving Average Calculator
The Weighted Moving Average (WMA) calculator can determine the weighted moving average of a given dataset based on the input vector of weights information. By providing the values in the dataset and their corresponding weights, you can calculate the weighted moving average over a specific period or time interval.
Reference
Traders generate trade direction information according to the weighted moving average (WMA) technical indicator and subsequently use this information to make decisions as to whether to buy or sell stocks. The WMA assigns less weighting to data points that are in the past and a higher weighting to more recent data points. The WMA is determined by multiplying every observation in a given data set by a preset weighting factor.
When provided with a list of sequential data, you can build the npoint weighted moving average (or weighted rolling average) by ascertaining the weighted average of every set of n successive points. For instance, let's say you have the following ordered data set:
9, 10, 14, 15, 13, 11, 9, 10
This set has a weighting vector as follows [1, 3, 7], where 7 is applied to the most recent term, 3 is applied to the midpoint term, and 1 is applied to the oldest term. As such, the weighted 3point moving average would be as follows:
12.455, 14.273, 13.636, 11.909, 9.909, 9.818
Weighted moving averages are typically employed to "smooth" chronological data while attaching a greater level of significance to the terms that are deemed to be the most important. Some weighted averages attach a higher value to more recent terms, while others attach a higher value to central terms.
Stock analysts frequently utilize the linearly weighted npoint moving average, which has the following weighting vector [1, 2, .., n â€“ 1, n].
If the quantity of terms in the initial data set is k and the quantity of terms employed in every average is n (i.e., the weight vector has a length of n), the quantity of terms (N) in the moving average series will be as follows:
N = k â€“ n + 1
For example, if you have a sequence of 50 stock prices and take a 10day weighted moving average of the prices, then the weighted moving average sequence will have 50 â€“ 10 + 1 = 41 data points.
What is Weighted Moving Average Calculator
A Weighted Moving Average (WMA) calculator is a tool used to calculate the average value of a time series data set over a specified number of periods, where each period is assigned a weight. The WMA differs from the Simple Moving Average (SMA) by assigning different weights to different data points, giving more importance to recent data.
Here's how a Weighted Moving Average calculator typically works:

Data Input: The calculator requires a series of historical data points, such as daily closing prices or other relevant values, for the asset or variable you want to calculate the moving average of. This data should cover a specific time period.

Setting the Period: You need to specify the number of periods over which you want to calculate the weighted moving average. For example, if you choose a 10day WMA, it will calculate the average based on the past 10 data points.

Assigning Weights: Unlike the SMA, each data point in the WMA is assigned a weight that reflects its importance. The most recent data point receives the highest weight, while the weight decreases as you move back in time. The sum of the weights should equal 1.

Calculation: The calculator multiplies each data point by its corresponding weight and then sums up the results. The resulting sum represents the weighted moving average value.

Displaying the Result: The calculator provides the calculated Weighted Moving Average as the output. It represents the weighted average value of the data series over the specified period, reflecting the importance of recent data.
Weighted Moving Averages are commonly used in technical analysis to identify trends and potential buy or sell signals. By assigning more weight to recent data, WMAs can quickly respond to market changes and provide a more timely indication of price movements.
Weighted Moving Average calculators can be found online or implemented in various charting platforms, trading software, or spreadsheet programs like Excel. Traders, analysts, and investors use these calculators to analyze historical price data and make informed decisions in the financial markets.
Weighted Moving Average Calculator Example
Certainly! The Weighted Moving Average (WMA) is another type of moving average that assigns different weights to each data point within a specified period. Let's consider an example of calculating the Weighted Moving Average for a stock using daily closing prices.
Assume we have collected the daily closing prices of a stock for the last 5 trading days. Here are the closing prices (in arbitrary units):
100, 105, 110, 115, 120
Step 1: Determine the time period and assign weights.
First, we need to determine the time period for which we want to calculate the Weighted Moving Average. For this example, let's use a 5day Weighted Moving Average.
Next, we need to assign weights to each data point. The weights can be any set of values that add up to 1 and reflect the significance or importance given to each data point. In our example, let's assign the following weights:
Day 1: 0.1 Day 2: 0.15 Day 3: 0.25 Day 4: 0.3 Day 5: 0.2
Step 2: Calculate the weighted sum of closing prices.
Next, we calculate the weighted sum by multiplying each closing price with its corresponding weight and summing the results.
Weighted Sum = (100 * 0.1) + (105 * 0.15) + (110 * 0.25) + (115 * 0.3) + (120 * 0.2) = 109.75
Step 3: Calculate the Weighted Moving Average.
The Weighted Moving Average is calculated by dividing the weighted sum by the sum of the weights.
Weighted Moving Average = Weighted Sum / Sum of Weights
In our example, the Weighted Moving Average is:
109.75 / (0.1 + 0.15 + 0.25 + 0.3 + 0.2) = 110
Therefore, the 5day Weighted Moving Average for this stock, based on the given data and weights, is 110.
Please note that the weights assigned can vary based on the analysis requirements and trading strategies. Additionally, the example used here is simplified for illustrative purposes, and in practice, larger data sets with more complex weightings are typically used for calculating the Weighted Moving Average.