Learn
One of the most commonly used indicators in equities trading, the moving average is a seemingly simple technical analysis tool that smooths out price data to identify trends. Calculating moving averages is easy, but understanding how to trade them requires some specialist knowledge.
There are two primary types of moving average: Simple Moving Averages (SMA) and Exponential Moving Averages (EMA). The SMA calculates average closing prices over a set number of periods, offering a straightforward representation of trend direction and removing random small fluctuations from the price data. The EMA is weighted to put more importance on recent prices, creating a trendline more responsive to recent price changes.
Traders use both simple and exponential moving averages to identify trends, support and resistance levels and potential reversal points. Crossovers between short-term and long-term moving can be used to generate buy or sell signals, and there are different standard period lengths used for different markets.
Moving averages are an example of a lagging indicator, one that reflects past changes in price. Although the moving average deals with past market information, it can still be used to generate forward-looking price signals in a number of ways, including crossovers and moving average convergence divergence. The greater the number of periods in the moving average, the further it lags and the less the influence of the most recent price changes. This smooths out noise, but also smaller trends, especially those that run counter to the main trend. An important skill when trading with a simple moving average is to match the timescale to the expected trade duration: because longer-term trends are made up of smaller sub-trends, the five-day moving average is unlikely to be of interest to traders looking to hold a position for months or years.
Lagging indicators also require special attention for CFD traders since we normally deal with short timescales, either intraday positions or very short-term multiday ones. That means longer term trends – while remaining important as background information about the market – don’t always have relevance to the shorter intraday swings CFD traders follow. Using shorter moving averages, for example one hour and five hours, or even 5 minutes and one hour, allows intraday CFD traders to apply the same principles to shorter term price action. Longer term moving averages can be used to bias your strategy in the direction of the prevailing trend, which could in theory increase the win rate for your strategy. Of course, prices can always move in either direction, and traders should be careful not to overextend.
Moving average convergence divergence is a popular momentum indicator used in technical analysis for equities or other markets such as forex and indices. It consists of two main components: the MACD line and signal line. The MACD line is calculated by subtracting the 26-period EMA from the 12-period EMA. The result is then used to plot the MACD line on a chart. The signal line, often a 9-period EMA of the MACD line, is plotted alongside it.
Traders use the MACD to identify potential trend reversals, momentum shifts, and the strength of a trend. When the MACD line crosses above the signal line, it is usually interpreted as a bullish signal, indicating potential upward momentum. Conversely, a cross below the signal line could be seen as a bearish signal. Additionally, the distance between the MACD line and the signal line (histogram) provides a visual representation of the strength of a prevailing trend. Traders often use the MACD in conjunction with other technical indicators to make more informed trading decisions.
A trader wants to open a position on the EUR/USD currency pair using MACD divergence as a signal. After analysing the EUR/USD chart, he notices a potential bullish signal when the MACD line crosses above the signal line at 1.095. This crossover suggests a potential upward momentum in the EUR/USD pair. Before entering the trade, he seeks additional confirmation from other indicators, such as checking for supportive chart patterns, key support and resistance levels, or oscillators like the RSI. In our example, the RSI is at 25, indicating potential oversold conditions despite the emerging uptrend seen with MACD.
With two bullish signals, the trader is confident his analysis is correct. Accordingly, he decides to enter a long position using a EUR/USD CFD, opening the contract at 1.095. The next task is managing the risk profile and position sizing. After checking recent price action, and preserving a 1:2 risk reward ratio, the trader sets his take profit at 1.097 and stop loss at 1.094. This is appropriate for a short-term, intraday position. Because the currency pair is highly liquid and the position is managed with a tight stop loss, he will likely use considerable leverage to maximise gains. Remember, using any kind of leverage increases your risk of losses. After a few hours of price action, the trade wins and our trader closes the contract once it creases the take profit level.
The role of moving averages in the stock market is an important one, as much of the technical side of stock trading relies on identifying longer term uptrends and downtrends. Simple moving average crossovers are some of the most useful signals for an identifying bull and bear markets. When the short term simple moving average crosses above the long term, this is normally seen as a bullish signal. Conversely, when the short-term average falls below the long-term line, this is viewed by most stock CFD traders as a bearish signal.
Sometimes traders will develop a system that exclusively uses moving averages to generate buy and sell signals, going long when the short-term average is trending upwards and above the long term, and short when it starts to trend down or crosses back below. These strategies may be effective but also require caution, and ideally confirmation with other trading signals such as candlestick patterns or oscillators.
Fundamental analysis can also give clues to the underlying prevailing trend, which is normally makes sense to follow, even if trading short term price fluctuations via CFDs. For example, if a stock has a strong fundamental case for price increases, a trader using the crossover trading strategy may choose to only follow the long signals and ignore short ones or use them to exit trades. Because the smaller trends that make up the prevailing trend will usually lean more towards long or short, it is advantageous to bias your trading towards the prevailing, longer-term trend.
The exponential moving average is slightly more sensitive to price action, as it weights the most recent changes over longer-term price data. This creates a slightly noisier signal but ensures that short term trends are more accurately captured in the trendline. The exponential moving average is an interesting choice for stock CFD traders, since day trading focuses more on recent price moves than longer term trends. Because the exponential moving average is more sensitive, it allows you to pick up new trends quicker and will generate more buy and sell signals than a simple moving average. This comes at the cost of increased noise and in theory a greater number of false positives: by testing your strategy on a demo account using live market prices you will get a better idea whether a given strategy is viable, or if it could potentially lead to losses.
The Displaced Moving Average (DMA) is a moving average, either simple or exponential, that has been extended backwards or forwards in time. This is a very common practice in technical charting, with support and resistance lines often extended into the future to find potential points for later reversals. A stock DMA allows traders to see the relation between the live price and trendline, potentially generating crossover signals between the live price chart and the DMA. These are then traded in a similar way to crossovers between long- and short-term moving averages, with the market price crossing below the DMA a bearish signal and a price moving above the stock DMA a bullish one. The DMA is intended to turn the lagging indicator into a forward-looking one, but sudden changes in price can render the trendline obsolete.
Moving averages are a useful indicator for stock CFD traders. The concept is simple, using a trendline to smooth out noise from price data and show only important trends. In this they are similar to non-time-based charting methods such as the point and figure chart, a chart which moves along its x axis when a sufficient price change is reached. The exact type of moving average you use will depend on your trading style, with the exponential moving average popular with CFD traders for its speed and sensitivity.
Moving averages are lagging indicators, so they do not provide forward signals of future trends, and accordingly are more popular with trend-following traders than mean reversion traders. This makes sense, since profitability in mean reversion strategies relies on identifying a changing trend early, just before it happens or in its first few moments. Conversely trend followers look to share in the price action of an existing trend, making lagging indicators more appropriate. Displaced moving averages extended forwards can also overcome some of the limitations of a lagging indicator, but traders must remember sudden price moves can make an old trendline obsolete.
MACD is probably the best-known moving average-based strategy, and every technical trader should have at least some understanding of how this strategy works. When using moving averages, simple or exponential, it is vital to make sure your time frame is appropriate – there is no point identifying a years-long trend if you want to close a position tomorrow. By matching the timeframe and number of periods to their trading style, and confirming any signals with an appropriate second indicator, moving averages can be a powerful tool for high-speed, technical trading.
Moving average crossovers are a widely used technical indicator that can generate long and short signals based on the crossover between shorter and longer-term moving average lines. This strategy involves both simple and exponential moving averages, with commonly used periods such as 50 and 200 for long-term averages, and five – 30 days for shorter term. A buy signal occurs when the shorter-term moving average crosses above the longer-term, indicating potential upward momentum. Conversely, a sell signal is generated when the shorter-term moving average falls below the longer-term. Traders often use moving average crossovers in conjunction with other technical and fundamental methods for more reliable signals, and the timeframes can be adjusted to suit different trading styles, such as swing trading.
The most commonly used time periods in moving average lines are 10, 20 and 30 days for short-term moving averages and 50, 100 or 200 for long-term averages. When choosing a moving average in the stock market you need to decide what timeframe your trade will take place over, in other words how long you are willing to hold the position. Traders, often superstitious, sometimes use well known sequences such as the Fibonacci sequence to select moving average periods. It is an open question whether or not this works.
The moving average crossover is a commonly used technical strategy where traders generate long and short signals by the crossover between a longer and shorter term moving average line. This strategy can be performed with either simple or exponential moving averages and on any period length. The strategy produces a buy signal where the shorter term moving average crosses above the longer term, and a sell signal when it falls below. Normally this strategy is used in conjunction with other technical and fundamental methods to produce more reliable signals.
Exponential Moving Averages (EMAs) are more sensitive to recent price action compared to the simple moving average, weighting the most recent changes over longer-term price data. This sensitivity allows EMAs to capture short-term trends more accurately, making them suitable for day trading where the focus is on recent price moves. EMAs generate more frequent buy and sell signals compared to SMAs but may also produce more noise and false positives. Traders often use EMAs to identify new trends quickly and fine-tune their strategies for shorter timeframes.