zenduck.me: Weighted Moving Average Calculator Good Calculators
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This weighted moving average (WMA) calculator can determine the weighted moving average of a given data set with respect to the input vector of weights information.
You can use the calculator in three simple steps:
- Enter the data values, separated by commas, spaces, or line breaks.
- Input the weights with each item separated by a comma.
- Click on the “Calculate WMA” button to determine the weighted moving average.
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 n-point 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 mid-point term, and 1 is applied to the oldest term. As such, the weighted 3-point 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 n-point moving average, which has the following weighting vector [1, 2, .., n – 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 – n + 1
For example, if you have a sequence of 50 stock prices and take a 10-day weighted moving average of the prices, then the weighted moving average sequence will have 50 – 10 + 1 = 41 data points.
You may also be interested in our Simple Moving Average Calculator or Exponential Moving Average Calculator