Moving averages are a statistical indicator that smooths price data by creating a series of averages over a defined number of periods. The calculation comes in several forms, including the simple moving average (SMA), exponential moving average (EMA), and weighted moving average (WMA). In an SMA, the closing prices for the last N periods are added and divided by N. In an EMA, more weight is given to recent prices, so the line reacts more quickly to new information. A WMA uses a different weighting scheme across the periods. The choice of method and the number of periods affects how smooth the line is and how sensitive it remains to recent moves.
On a price chart, moving averages help illustrate the direction of the price trend over time and can define a smoothing band around price action. A rising average generally indicates upward momentum over the selected horizon, while a falling average indicates downward momentum. When a shorter-term moving average crosses above a longer-term moving average, some practitioners view this as a crossover event that may correspond to a change in trend direction. Moving averages are often used with other indicators, such as MACD (moving average convergence divergence), which is a momentum indicator derived from differences between EMAs.
Important caveats: moving averages are lagging indicators because they rely on historical data; they reflect past price behavior rather than predicting future moves. They are most useful when interpreted within a broader analytic context and across multiple time frames.
On a price chart, the 50-day simple moving average is plotted to illustrate the longer-term direction and to show how price interacts with the average over time.
Simple moving average (SMA) · Exponential moving average (EMA) · Weighted moving average (WMA) · Moving average convergence divergence (MACD) · Crossover · Trend