Moving averages are one of the most commonly used technical indicators in stock, futures and forex trading. Market analysts and traders use moving averages to help identify trends in price fluctuations, smoothing out the noise and short-lived spikes (from news and earnings announcements, for example) for individual securities or indexes. There are different types of moving averages, calculated in different ways and over different time periods, which reveal different information for traders. The type of moving average and measurement period used determine the strategies a trader implements.
Common Moving Averages Periods
Traders and market analysts commonly use several periods in creating moving averages to plot on their charts. For identifying significant, long-term support and resistance levels and overall trends, the 50-day, 100-day and 200-day moving averages are the most common. Based on historical statistics, these longer-term moving averages are considered more reliable trend indicators and less susceptible to temporary fluctuations in price. The 200-day moving average is considered especially significant in stock trading. As long as the 50-day moving average of a stock price remains above the 200-day moving average, the stock is generally thought to be in a bullish trend. A crossover to the downside of the 200-day moving average is interpreted as bearish.
The 5-, 10-, 20-, and 50-day moving averages are often used to spot near-term trend changes. Changes in direction by any of these shorter-term moving averages are watched as possible early clues to longer-term trend changes. Crossovers of the 50-day moving average by either the 10-day or 20-day moving average are regarded as significant. The 10-day moving average, plotted on an hourly chart, is frequently used to guide traders in intraday trading.
Some traders use Fibonacci numbers (5, 8, 13, 21 ...) to select moving averages.
Types of Moving Averages
All moving averages are utilized to identify significant support and resistance levels. Traders and market analysts watch for crossovers of longer-term moving averages by shorter-term moving averages as possible indicators of trend changes in intraday trading and in regard to long-term trends. Most moving averages act as both trendline indicators and as the building blocks of more ambitious technical tools.
There are numerous variations of moving averages. They can be calculated based on closing price, opening price, high price, low price or a calculation combining those various price levels. Most moving averages are some form of either the simple moving average (SMA), which is just the average price over a given time period, or the exponential moving average (EMA), which is weighted to favor more recent price action.
Simple moving averages can be rather slow to catch up if large price swings occur. More traders look at exponential moving averages instead, as they react more quickly to price changes, therefore providing a more accurate reading. Time is of the essence with trading any type of security. An EMA and double exponential moving average (DEMA) both reflect the current price trend for a security in a more up-to-date reading.
Since moving averages by nature are lagging indicators, getting the readings up to speed is important. The EMA gives more weight to the most recent prices, thereby aligning the average closer to current prices. EMA is typically calculated for 12- or 26-day periods for short-term traders, and the ever-popular 50-day and 200-day EMA is used by long-term investors. While the EMA line reacts more quickly to price swings than SMA, it can still lag quite a bit over the longer periods.
DEMA helps to solve the lagging issue, bringing a moving average line closer to the current fluctuations in price. This metric is calculated not just by doubling the EMA but by using the following complex formula: DEMA = 2*EMA - EMA(EMA), where the current EMA is a function of the EMA factor. Essentially, this means even more weight is applied to the recent data, bringing the DEMA line into closer correlation with the current price. Traders see DEMA crossovers before EMA and SMA crossovers, allowing for quicker reaction times with trades.
One of the most common trading strategies traders use with the DEMA tool is identifying price movements when a long-term and short-term DEMA line cross. For instance, if a trader sees that the 20-day DEMA comes down and makes a crossover of the 50-day DEMA, which is a bearish signal, he or she may sell long positions or take on new short positions. Conversely, the trader enters long positions and exits short positions when the 20-day DEMA crosses back up and over the 50-day.
Drawbacks of Moving Averages
Moving averages are backward-looking by nature. While EMAs can reduce the lag effect on developing trends, they still rely on past data that can never be applied to the future with complete confidence. Securities sometimes move in price cycles and repeat behavior, but past trends that are plotted with a moving average may have no relationship to future movements.
Additionally, the increased reliance on recent price movements with an EMA tend to make it more sensitive to false trading signals, or whipsaws, than an SMA. For this reason, an EMA may require further confirmation before a trade can be identified.
There is also room for user error with any EMA. Traders must decide how long of a time interval to apply to their formula, and they must also decide how heavily to weight towards recent prices (and which prices are considered to be recent). False signals can be generated through inappropriate parameters.
For more, read our Moving Averages tutorial.