A Weighted Moving Average (WMA) is a statistical method used to analyze data points by giving different weights to each value. Unlike a simple moving average, where all values are treated equally, WMA assigns more importance to recent data, making it more responsive to changes. This is particularly useful in fields like finance and economics for forecasting trends. To calculate a WMA, you multiply each data point by a predetermined weight and then sum these products. Finally, you divide this total by the sum of the weights. This approach helps in smoothing out fluctuations while highlighting significant trends over time.