Moving Average Calculator

Moving Average Calculator

Calculation Results

Data Point Value Moving Average

What is a Moving Average?

A moving average (MA) is a widely used statistical calculation used to analyze data points by creating a series of averages of different subsets of the full data set. In finance and technical analysis, it is a stock indicator that is commonly used to help smooth out price action by filtering out the "noise" from random short-term price fluctuations.

How the Simple Moving Average (SMA) is Calculated

The Simple Moving Average is the easiest type of moving average to construct. It is calculated by adding up the values in a time series and dividing that sum by the number of time periods (N). The formula is:

SMA = (A1 + A2 + … + An) / n

Where 'A' represents the data value at a specific period and 'n' is the total number of periods used in the average.

Example Calculation

Suppose you want to calculate a 3-day moving average for the following closing prices: 10, 12, 14, 16, 18.

  • Day 3: (10 + 12 + 14) / 3 = 12.00
  • Day 4: (12 + 14 + 16) / 3 = 14.00
  • Day 5: (14 + 16 + 18) / 3 = 16.00

Why Use Moving Averages?

Moving averages are lagging indicators because they are based on past prices. However, they are invaluable for identifying trends and reversals. A rising moving average indicates that the security is in an uptrend, while a declining average indicates a downtrend. Analysts also use crossovers—where a short-term moving average crosses a long-term moving average—as signals for potential buying or selling opportunities.

function calculateMovingAverage() { var rawData = document.getElementById("seriesData").value; var period = parseInt(document.getElementById("maPeriod").value); var container = document.getElementById("maResultContainer"); var summary = document.getElementById("maSummary"); var tableBody = document.getElementById("maTableBody"); // Clean data input var values = rawData.split(/[\s,\n]+/).filter(function(item) { return item.trim() !== "" && !isNaN(parseFloat(item)); }).map(Number); if (values.length === 0) { alert("Please enter valid numeric data points."); return; } if (isNaN(period) || period values.length) { alert("The period cannot be greater than the number of data points."); return; } var averages = []; tableBody.innerHTML = ""; for (var i = 0; i = period – 1) { var sum = 0; for (var j = 0; j < period; j++) { sum += values[i – j]; } var ma = sum / period; cellMA.innerText = ma.toFixed(2); cellMA.style.fontWeight = "bold"; cellMA.style.color = "#27ae60"; averages.push(ma); } else { cellMA.innerText = "—"; cellMA.style.color = "#999"; } row.appendChild(cellIndex); row.appendChild(cellValue); row.appendChild(cellMA); tableBody.appendChild(row); } summary.innerHTML = "Total Data Points: " + values.length + "" + "Period Selected: " + period + "" + "Last Moving Average: " + (averages.length > 0 ? averages[averages.length – 1].toFixed(2) : "N/A"); container.style.display = "block"; }

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