Weighted Average
Candlefocus EditorWeighted average is a method used to give different values in a dataset more or less influence over the overall mean. By assigning a "weight" to each value, the mean calculation gives a more accurate reflection of the total than a simple average which treats all values equally. Weighted averages are commonly used in fields such as finance, statistics, engineering, and research.
In a weighted average, each data point is multiplied by its assigned, or "weighted", value, and all of the product values are then added together. This value is then divided by the total number of weighting factors to yield the overall mean. For example, a 60% weight factor muliplied by the value of 5 yields a 3 product. If there are 3 data points with their respective weighting factors, then the weighted average would be the sum of the three values divided by the sum of their corresponding weighting factors.
Investors use weighted averages when computing the cost of stocks bought at different prices. This allows investors to establish baseline values for evaluating stock performance. Further, weighted averages often require more complex computations and yield more accurate results than the use of a simple average.
Weighted averages can be used to evaluate data that changes over time, or in calculation of composite indices. For example, the Dow Jones Industrial Average price-weighted index is a weighted average of the prices of 30 of the largest stocks traded on the New York Stock Exchange.
Overall, a weighted average allows for a more accurate calculation of a data set than a simple average. Assigning a weight to data points enables the user to distinguish between the relative importance or frequency of the values. Investors use weighted averages for tracking stock purchasing prices and to establish baseline values for the performance evaluation of stocks. Furthermore, weighted averages generally yield a more accurate result when compared to simple averages, particularly for data that changes over time.