What does "Exponential Moving Average" mean?
Table of Contents
The Exponential Moving Average (EMA) is a method used to smooth out data points over time. It gives more weight to recent data, making it more responsive to changes than a simple average. This means that when new information comes in, it can quickly influence the average, while older data becomes less important.
How It Works
To compute the EMA, you start with an initial value. As new data comes in, you update the average by applying a formula that takes into account the new value and the previous average. This allows for a real-time update that reflects the latest trends in the data.
Uses
The EMA is popular in various fields, including finance and data analysis, because it helps identify trends and patterns. It can provide insights into data that fluctuates frequently, helping users make informed decisions based on the latest information. In assessments of quality or performance, utilizing EMA can help filter out noise and highlight genuine changes over time.