Moving Average
Calculate simple moving averages online free. Enter comma-separated data and window period to smooth trends, analyze time series, and identify patterns with interactive charts and breakdown tables.
About This Calculator
The Moving Average Calculator computes the simple moving average (SMA) of any numerical dataset. A moving average smooths out fluctuations in data by averaging a sliding window of consecutive values, making it easier to identify trends, cycles, and patterns. This is a fundamental tool in technical analysis, time series forecasting, and statistical data smoothing.
Simply enter your data as a comma-separated list (e.g. stock prices, daily temperatures, sales figures) and choose a window period. The calculator computes the moving average for every window position, showing the trend line on an interactive chart alongside the original data points. The breakdown table lists each window's average for detailed analysis.
Moving averages are essential in finance for identifying trend direction and support/resistance levels, in economics for smoothing GDP or employment data, in weather forecasting for temperature trends, and in inventory management for demand smoothing. The simple moving average gives equal weight to each data point in the window.
How to Use
Enter data values as a comma-separated list. Set the window period (must be at least 2 and no more than the number of data points). Click "Calculate Moving Average" to see the smoothed results, chart overlay, and per-window breakdown. The URL saves your inputs for sharing or bookmarking.
Frequently Asked Questions
What is a moving average?
A moving average (MA) is a calculation that averages a subset of data points within a sliding window as it moves through the dataset. It smooths out short-term fluctuations and highlights longer-term trends or cycles. The simple moving average (SMA) is calculated by taking the arithmetic mean of a set of values over a specified number of periods.
How do I use the moving average calculator?
Enter your data values as a comma-separated list (e.g. 10, 12, 15, 14, 18, 20) and specify the window period (e.g. 3). The calculator will compute the moving average for each window position and display the final average. A line chart compares the original data against the smoothed moving average line.
What is the difference between simple and exponential moving averages?
This calculator computes the simple moving average (SMA), which gives equal weight to all data points in the window. An exponential moving average (EMA) gives more weight to recent data points, making it more responsive to new information. SMA is commonly used for identifying trends, while EMA is preferred for short-term trading signals.
How do I choose the right window period for moving average?
The window period depends on your data and analysis goals. Shorter windows (e.g. 3-5 periods) react quickly to price changes and are used for short-term trend detection. Longer windows (e.g. 20-200 periods) produce smoother lines that highlight major trends. Common choices are 10, 20, 50, 100, and 200-day moving averages in finance.
What are common uses of moving averages?
Moving averages are widely used in technical analysis of stock prices and trading, time series forecasting, weather data analysis, inventory demand planning, signal processing to remove noise, economic indicator smoothing, and any application where identifying trends in noisy data is important.
Can I use the moving average calculator with any dataset?
Yes, the calculator works with any numerical dataset. Enter your values as comma-separated numbers and choose a window size. The window size must be at least 2 and cannot exceed the number of data points. The calculator works for financial data, temperature records, sales figures, test scores, or any time-series data.
Is this moving average calculator free?
Yes, this moving average calculator is completely free to use with no registration, downloads, or hidden charges. Share your results via URL bookmarking.
How is the moving average calculated?
The simple moving average (SMA) is calculated by summing all data points within a window and dividing by the window size. The window then shifts forward by one period, discarding the oldest value and including the next one. For example, with data [10, 12, 15, 14, 18, 20] and window 3: SMA1 = (10+12+15)/3 = 12.33, SMA2 = (12+15+14)/3 = 13.67, and so on.