One of the oldest and most commonly used technical indicators is the Moving Average. Traders can take advantage of low-risk, high-reward trading opportunities by using this technical indicator.
Trading is not easy and certainly not simple. Underestimating the risks in trading will cost you big, especially if you don’t have any trading tools or strategies to use. These tools or strategies are essentially useful in trading as they can help you indicate what your next move will be.
Some of the most useful tools include the Moving Average Convergence/Divergence (MACD), Trend Lines, Relative Strength Index, Fibonacci Retracements, and the Moving Average.
It may be good to use them sometimes or consistently, but the most important thing is to apply them correctly each and every time. Using them improperly can lead to disastrous results.
Each of these tools specializes in certain situations, like when the market is trending. And when the market is trending, what could be the most ideal tool to use?
Enter Moving Average. This can smooth the price data to form a trend-following indicator. It doesn’t predict price direction, but finds the current direction with a lag. Despite the lags that are based on past prices, moving average can help smooth price action and rid out the noise.
There are two most popular types of moving averages, which are Simple Moving Average (SMA) and Exponential Moving Average (EMA). Both indicators can be used to determine the direction of the trend or the potential support and resistance levels.
Here is an example of a chart with both SMA and EMA on it. The blue line is the SMA, while the red line is the EMA. Notice that the EMA is closer to the real moment of data points? That is because EMA is more accurate than SMA.
Simple Moving Average
You can get the SMA by computing the average price of a security over a specific number of periods. Usually, moving averages are based on closing prices. So, a 5-day simple moving average is the 5-day sum of closing prices divided by 5.
Just like the name, as the average moves, drop the old data as new data comes available. The averages will move along the time scale. Here is an example of a 5-day moving average developing over 3 days.
- Daily Closing Prices: 11,12,13,14,15,16,17
- First day of 5-day SMA: (11 + 12 + 13 + 14 + 15) / 5 = 13
- Second day of 5-day SMA: (12 + 13 + 14 + 15 + 16) / 5 = 14
- Third day of 5-day SMA: (13 + 14 + 15 + 16 + 17) / 5 = 15
The first day simply covers the last 5 days. The second day of the SMA drops the first data point, which is 11, and adds the new data point 16. Then, the third day continues by dropping the first data point, which is 12, and adding the new data point which is 17.
Over the total of 7 days, prices gradually increase from 11 to 17. The moving average also increases from 13 to 15 over a 3-day period. And notice that each moving average value is just below the last price. For example, the moving average for day one equals 13 and the last price is 15. Prior the 4 days, prices were lower and this lead to the moving average to lag.
Exponential Moving Average
The difference of EMA from SMA is that it reduces lag by applying more weight to recent prices. The weight applied to the most recent price depends on the number of periods in the moving average.
The first thing to do to get the initial EMA value is calculate the simple moving average, as this will be your starting point.
The second step is to calculate the weighting multiplier. If you are calculating for a 10-period EMA, apply an 18.18% weighting to the most recent price. If you are doing a 20-day EMA, apply a 9.52% weighting to the most recent price. Something that is worth noticing is the weighting for the shorter time period, which is 10 days, is higher than the weighting for the longer time period. Remember, the weighting drops by half every time the average period doubles.
For the third step, calculate the EMA for each day between the initial SMA, which is your starting point, and the EMA for today using the price, the multiplier, and the previous period’s EMA value. Here is the formula for a 10-day EMA period:
The formula for the EMA includes the previous period’s EMA, which also includes the EMA before it, and so on. As each previous EMA value accounts for a small portion of the current value, the current EMA value will change based on how much past data you use in your calculation.
If you want your EMA 100% accurate, then use every data point that the stock has ever had. This means calculating from the first day that the stock ever existed. You must have a lot of time on your hands if you consider doing this, but it tells you one thing, the more data points you use, the more accurate your EMA will be.
It’s clear that there are differences between the two moving averages. But sometimes, when we see something more advanced and complicated, we would think that it is far better than the other. In this case, it is not. EMA has less lag, which therefore, more sensitive to recent prices and recent price changes. Despite this, EMA will turn before SMA.
However, SMA represents a true average of prices for the entire time period. Considering this, SMA may be more suitable in determining the support or resistance levels
Before choosing on which moving average to use, it’s important to know that their preferences depend on the objectives, analytical style, and time horizon. It is ideal to experiment with both kinds of moving averages as well as different time periods to find which is the best suitable.