For a technical trader the trend is utterly important. Several indicators (and methods) have been developed to help us technicians in determining whether the market is trending or trading. Knowing the market conditions helps us to determine what kind of technical tools we can use in our trading. In a trending market the use of trend indicators such as Moving Averages (MA), MACD and ADX are well suited. While the use of oscillators in a trending market could yield disappointing results. These tools are better suited in a trading market or market reversals.
The Moving Averages (MA) are the most common indicators used by traders. Plotting key moving average levels on your chart helps traders to get a first quick impression of the direction of the market. MA work by calculating the average value of price over a selected period. Because an average of past price is used, you get a “smoothed out” representation of the price. Besides offering help to what the direction of the trend is, Professional traders often use MA to find dynamic support and resistance levels.
Moving Averages are lagging indicators, meaning that they respond with a delay to market movements. The longer the selected time period, the bigger this lag effect is. A cross-over of different moments can signal a change in trend and for starting traders an trend following trading strategy based on MA cross-overs is often one of the first trading strategies they perform.
There are three (main) types of moving averages:
- Simple Moving Average (SMA)
- Weighted Moving Average (WMA)
- Exponential Moving Average (EMA)
Simple Moving Average (SMA)
This the most common moving average. Often in financial literature when they talk about moving averages, they refer to the Simple Moving Average (SMA). The SMA is nothing more than the average price for the interval period. The SMA-200 is one of the most powerful moving averages, and a cross of this key level often indicate a switch in long term trend.
The equation is:
Weighted Moving Average (WMA)
A different type of moving average is the Weighted Moving Average (WMA). Where the SMA attributes the same weights each observation, the WMA values gives more weight to the most recent observations. If for example we use a WMA-5, meaning the WMA is based on 5 observations, the last observation with have a weight of 5, the observation before that (t-1) will get 4, (t-2) get 3, etc. In equation form it will look like this.
By giving more weight to the most recent observations the WMA will respond more quickly to a recent switch in trend.
Exponential Moving Average (EMA)
The exponential moving average (EMA) also attributes more weight to the most recent observations. But does this slightly different than the WMA discussed above. The equation of how the EMA does this is the following:
What this indicator basically does is taking the difference between the current price and the EMA of the last trading period. This difference is multiplied by the constant factor k and added to the last EMA. The weighting effect in this equation is done by the constant factor k. An observation of 5-periods away has much less weight because it is roughly multiplied 5 times with the constant.
The use of EMAs is popular among professional traders. The weighting effect in the EMA its equation allows it to adapt to a fast moving market. Especially the EMA 20, 50 and 200 periods are commonly used. Two ways we use EMAs in trading is to identify trend, and to provide a level of dynamic support and resistance (which will not be discussed in this post).
The position of the market compared to key EMA levels often says something about the market. It is often said that:
- When the market is above the 50 EMA the market is bullish
- When the market is below the 50 EMA the market is bearish.
Number of periods
A moving average shows us what the trend is of the market. By selecting a short moving average – meaning only the most recent observations are used – we get an indication of what the short term trend is. Taking a lot of observations in the moving average would give us insight in the more long-term trend. A first question that will arise is what do we consider short, and what long? Common practice is that short is considered three to twenty periods, medium term: twenty to fifty, and for moving averages longer as fifty are often considered long-term.
The 200-day SMA is one of the most important moving average for the long-term. If the market is moving above the 200-day SMA, the uptrend is still intact. If a break occurs this is considered as a strong signal that the uptrend is broken and the market might be ready for a trend in opposite direction.
Combining multiple moving averages
In the introduction of this post we touched upon the use of different types of technical indicators in different types of markets. It was said that a trend indicator as the MA works well in a trending market, but it doesn’t when the market is ranging. This is exactly where a weakness of the MA lays. When the market is moving sideways, the moving averages will also move more or less horizontal. What happens is that you easily get many crossings of the market with the MA, giving false trading signals.
Combining varies moving averages can be used to determine the direction of the trend. A method developed by Charles LeBeau and David Lucas involves using a 4-, 9- and 18-day moving average to determine the direction of the trend. According to their research the direction is:
Uptrend: MA(4) > MA(9) > MA(18)
Downtrend: MA(4) < MA(9) < MA(18)
Ranging 1: MA(4) < MA(9) > MA(18)
Ranging 2: MA(4) > MA(9) < MA(18)
You can also use two MA for this, but using three MA will give a better picture of the market. This is because we can determine if the market is in a ranging state, something that you can’t do with just two MA.
This leaves is with a somewhat weird paradox. On the one hand we use moving averages to determine the trend, and on the other hand we use it to generate buy- and sell opportunities. Especially since we determined that moving averages are trend indicators and should only be used in a trending market (due to the lagging character imbedded in moving averages). This should not be too much of a problem if we use the method described by LeBeau and Lucas to determine whether we are allowed to use the RSI or not. Also for the generation for buy- and sell signals it shouldn’t lead to any problems if for example we add a filter only to trade if the ADX also signals a ‘go’.
Generating buy and sell signals
By combining different moving averages we can build a trading strategy that generates buy- and sell signals. For this a short, medium and longer term moving average is used (depending on if you want to use two or three MA). A buying signal occurs when the MA(short) breaks upwards through the MA(long). A selling signal is generated when the MA(short) breaks the MA(long) downwards. Because the MA are constructed on different time frames, they will cross-over when a strong price directional thrust is taking place. How easy a MA is crossed depends on the selected period. The longer this period, the less tight the MA will follow the market and therefore it’s likely to generate less cross-overs. Using a short timeframe will generate a lot more cross-overs, but often also more false signals.
So the question is how many periods should we use for the short, medium and long term moving averages? The disadvantage is that trading systems like these already have a lagging character. By using several MA and wait for them to cross, this lagging character will only become stronger, we build lagging-effect on lagging-effect. On the other hand, the use of multiple MA will generate less signals, but the quality is often better. This trade-off of period between a larger lagging effect versus less false signals requires traders to do extensive back testing on their strategy to optimize this. It also depends on a risk-appetite and trading style different for each trader.
The first pullback after a MA crossover can be a good entry point for swing traders.