Pros & Cons of using Simple Moving Averages
When you consult stock traders and ask them about the keys to profitable trades, you’ll likely get conflicting advice. Every trader embraces a particular investment strategy. Whether it’s the successful one or not, you can’t really tell. The stock market is an unpredictable investment ground that there is actually no textbook approach.
The simple moving average (SMA) method as an example appears to be the near-perfect stock-investing strategy. By analyzing the moving averages of a stock, you can see the trend or momentum.
Thus, it wouldn’t be as complicated to make your buy or sell decisions. But before you fully adopt this tool, you need to know that there are hidden risks in simple moving averages.
What are simple moving averages?
ALL the various investment strategies you hear about are meant to counter market uncertainties or volatility. You should note, however, that not every investment strategy is appropriate for every specific situation.
By definition, a moving average is the average price of a stock or equity issue over a given period of time. Stock traders look at the moving averages to monitor trend or follow the price movement of a particular stock, whether up or down. Moving averages can also serve as the support or resistance levels.
The common moving average lengths are 10, 20, 50, 100 and 200 days depending on the trader’s time horizon. The said lengths can be applied to any chart. During an upward trend, most traders would view the 50-day, 100-day, and 200-day moving average as the support level or the floor price. Inversely, the moving average is taken as the resistance level or the ceiling if the stock price touches this level before dropping again.
Given the above, you can make out the general rule when using simple moving averages. Whenever the stock price is above a moving average, there is an upward trend. If the stock price is below a moving average, the trend is down. Since moving averages can be as short as 10 days or longer, a moving average can either an uptrend or downtrend.
Computing for the simple moving average is not complicated. Since it’s basically a series of numbers, add up them up and divide the total by the number of data points. If for example, you want to calculate a 10-day average stock price, add the 10 days price and divide the sum by 10. Each time, the SMA is headed for the current date but provides a smoothed historical price movement.
Pros & Cons of using Simple Moving Averages
Always keep in mind that stock investing is not without risks. There are advantages and disadvantages in using the various investment strategies including simple moving averages.
Here are some of the pros and cons of this investment strategy, according to Kelvin Wong, Chief Technical Strategist for Asia, City Index.
The PROS of using simple moving averages
“SMA acts as a simple mathematical gauge to determine price action trends. For example, the short-term trend of a stock is up if it prices are above an upward sloping 20-day Moving Average and vice versa for a short-term down trending stock where its prices are below a downward sloping 20-day Moving Average.”
“It also acts as a gauge of trend change/reversal,” said Wong.
Wong also added that simple moving averages provide “dynamic areas of support and resistance for trending price actions where potential set up on entry levels can be identified at such areas”. “For example, a strong up trending stock tends to find support in pull-back/mean reversion decline in price action on its 20 or 50-day Moving Averages. On the contrary, strong down trending stock tends to stall at resistance in a squeeze up/mean reversion rebound in price action on its 20 or 50-day Moving Averages,” he said.
On the other hand, Wong points out that moving averages will not be able to determine support and resistance levels when the asset classes are undergoing a sideways configuration phase.
The CONS of using simple moving averages
“Market participants assume that the commonly use time parameters of 20, 50, 100 and 200 can be effectively applied to all asset classes. However, different asset classes have different time cycles and volatility and even within the same asset classes such as stocks,” said Wong. “For example, a 50-day Simple Moving Average may act as support for DBS but it a similar 50-day Simple Moving Average may not offer good support for Capitaland.”
At the same time, Wong explains that simple moving averages have a “lagging effect” because it is derived from past data. “For example, to calculate a 20-day Simple Moving Average, add the closing prices over a 20-day period and divide by 20. A new data point for the 20-day Simple Moving Average is being input by adding the latest data on the 21st day and removing the 1st data point. The weightages of all historical data points used in the calculation of a Simple Moving Average are equal even if market participants would like to put more emphasis on the latest historical data.”
Understand the function of Simple Moving Averages
Stock traders make use of the simple moving average to identify trends. It’s also a good way to monitor momentum and find the all-important support or resistance levels. But as discussed, there are certain factors which should be considered.
The method is undeniably “trader-friendly” except that it is a lagging indicator. SMAs can establish trends but are not capable of predicting new ones. But one simple rule stands out. Many traders will hold an asset for a longer period when a stock price is trading above a moving average. However, this rule still does not ensure the trend will tilt in favor of the trader.
Therefore, you need to understand the functionality of simple moving averages before using it. When you’re doing actual trading, it is important not to overlook valuable information outside of the trend you see.
Because of its limitations, successful traders often incorporate the simple moving averages strategy with other investment strategies to manage their stock portfolio better.
City Index’s Wong recommends investors also look for other alternatives such as using graphical supports and resistances such as trendlines or channeling techniques, using Adaptive Moving Average (AMA) to account for volatility, and using Exponential Moving Average (EMA) to reduce the lagging effect from SMA.
“AMA will follow prices more closely when price swings are relatively small and when price swings widen due to higher volatility, as the AMA will adjust accordingly and follow prices from a greater distance,” explains Wong. “In the computation of the EMA, the latest and most recent data will have a higher weightage compared with earlier data points. That’s why EMAs react more significantly to recent price changes than SMAs.”