Moving averages are used in technical analysis to identify trends in stock and commodity prices. There are three types: simple, linear weighted, and exponential. SMA is based on the average price over a specific period, while LWA and EMA compensate for recent prices. Moving averages are represented graphically on charts and can indicate an upward or downward trend. Traders can also plot short-term and long-term moving averages on the same chart to identify trends.
Moving averages in technical analysis help stock traders and others in the financial management industry identify trends in changes in stock and commodity prices in the open market. There are three types of moving averages in technical analysis: simple moving average (SMA), linear weighted average (LWA), and exponential moving average (EMA). Moving averages are some of the most frequently used technical indicators in security analysis: Technical indicators are statistics derived from market data used to predict changes in financial assets or economies. Each average is calculated based on the closing price of a security or other financial instrument over a given period of time. Financial analysts then plot averages on a chart or graph and look for price trends based on fluctuations at points on the chart.
SMA is calculated based on the average price of a stock or commodity over a specific period of time. It is constantly “on the go” because as new close prices become available, the older close price is pushed down. For example, the first day of a five-day moving average is based on the stock’s last five closing prices. Each day, a new closing value is added, the oldest closing price is lowered, and a new five-day average is calculated. Moving averages in technical analysis of this type provide an overview of the price of a stock or commodity over the time period used.
One criticism of the SMA is the fact that each closing price has the same weighting in determining the moving average. In fact, the most recent prices should carry more weight because they are the most indicative of future trends. LWA and EMA are two moving averages developed to compensate for this discrepancy.
The linear weighted average is calculated to reflect the importance of recent prices. Each closing price is multiplied based on its position in the data field. For example, when calculating a five day average, the most recent closing price is multiplied by five, the second most recent is multiplied by four, etc. These values are then added together and divided by the sum of the multipliers. In this case, the sum of the multipliers would be 15 (5 + 4 + 3 + 2 + 1 = 15).
The exponential moving average is the most complicated of the moving averages in technical analysis. It is based on a convoluted equation involving SMA, the current price of the security, an attenuation factor to account for price fluctuations, and the number of time periods. Fortunately, most quantitative analysis software packages and spreadsheets have the ability to calculate this average for traders. The EMA is sensitive to new data inputs and as a result provides a more accurate forecast of price changes than the SMA.
Once these moving averages are calculated in technical analysis, they are represented graphically on charts. A chart showing an upward sloping moving average coupled with a price that is above the moving average indicates an upward trend for a stock or commodity. Alternatively, a downward sloping moving average combined with a price below the moving average indicates a downtrend and usually prompts traders to sell.
Traders can also plot short-term moving averages and long-term moving averages on the same chart, such as a chart containing a stock’s five-day moving average and 10-day moving average. If the short-term moving average chart points are higher than the long-term moving average, the security’s prices show an upward trend. Conversely, a short-term moving average below the long-term moving average may indicate a downtrend.
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