Simple & exponential moving averages

Moving averages are commonly used in technical analysis to identify trends and potential entry and exit points for trading. There are two main types of moving averages: Simple Moving Average (SMA) and Exponential Moving Average (EMA). This article will describe the key differences between these two types of moving averages, their advantages and disadvantages, and provide examples of trading strategies and observed patterns based on these indicators.

Simple Moving Average (SMA)

A simple moving average (SMA) is calculated by adding up a set of closing prices and dividing by the number of periods used. For example, a 10-day SMA is calculated by adding up the closing prices for the past 10 days and dividing by 10. The resulting value is plotted on a chart, and this process is repeated for each subsequent day.

SMA = (Sum of Closing Prices over N periods) / N

N is the number of periods you want to calculate the SMA.

The sum of Closing Prices over N periods is the total of the closing prices for the previous N periods (e.g., if you are calculating a 20-period SMA, you would add up the closing prices for the previous 20 periods)

Let's say you want to calculate a 10-day SMA of the closing prices for a currency pair. Take the sum of the closing prices over the previous ten days and divide that by 10 to get the SMA for the current day.

For instance, if the closing prices for the previous ten days were: 1.1000, 1.1020, 1.1050, 1.1005, 1.0990, 1.0965, 1.0980, 1.0950, 1.0910, 1.0905, then the 10-day SMA for the current day would be:

SMA = (1.1000 + 1.1020 + 1.1050 + 1.1005 + 1.0990 + 1.0965 + 1.0980 + 1.0950 + 1.0910 + 1.0905) / 10
SMA = 1.0965

So the 10-day SMA for the current day would be 1.0965.

Note that as each new closing price is added to the calculation, the oldest closing price is dropped, and the SMA "moves" forward in time. This is why it's called a moving average.

The SMA is a lagging indicator because it is based on past prices. Therefore, it is less responsive to recent price changes and can be slower to identify new trends. However, it is also more stable and less prone to whipsaws and false signals when the price quickly changes direction.

Exponential Moving Average (EMA)

An exponential moving average (EMA) is similar to an SMA but places more weight on recent prices. This means that EMAs are more responsive to price changes than SMAs. The EMA calculation formula is more complex, but most charting software and trading platforms do this automatically.

EMA = (Price - EMA_prev) x (2 / (n + 1)) + EMA_prev

Price: the current price of the asset being analyzed
EMA_prev: the previous EMA value (or the initial EMA value, which is typically set to the simple moving average of the first n values)
n: the number of periods used for the calculation (e.g., 10, 20, 50)

The EMA calculation is iterative, meaning that each new EMA value depends on the previous EMA value. Therefore, the initial EMA value is typically calculated using a simple moving average of the first n values.

The EMA can be more useful in identifying trends early and provide more accurate signals for entering and exiting trades. However, it is also more prone to whipsaws and can be less stable than SMAs.

Key differences

The key difference between SMAs and EMAs is how they are calculated and the weight given to each data point. SMAs give equal weight to all periods in the calculation, while EMAs give more weight to recent periods. As a result, EMAs are more responsive to recent price changes but can be less stable.

Advantages and disadvantages

The advantages of using SMAs are that they are more stable and less prone to whipsaws. They help identify long-term trends and can be used as support and resistance levels. However, SMAs are slower to respond to recent price changes and may miss short-term opportunities.

The advantages of using EMAs are that they are more responsive to recent price changes and can identify trends earlier. In addition, they can provide more accurate signals for entering and exiting trades. However, EMAs are less stable and more prone to whipsaws. They may also be more difficult to interpret because they can generate more signals than SMAs.

Here's a summary of the key differences and the advantages and disadvantages:

Exponential Moving Average (EMA)
Simple Moving Average (SMA)

Calculation

More weight is given to recent data
All data points are treated equally

Formula

EMA = (Close - EMA(previous)) x multiplier + EMA(previous)
SMA = (Sum of Closing Prices over N periods) / N

Sensitivity

More responsive to recent price changes
Less responsive to recent price changes

Smoothing

Smooths out noise and fluctuations
Less effective at smoothing out noise and fluctuations

Lag

Less lag reacts faster to trend changes
More lag reacts slower to trend changes

Usefulness

Useful for short-term trading
Useful for long-term trend analysis

Signal accuracy

More likely to generate false signals
Fewer false signals, but may lag behind price action

Risk management

More sensitive to price movements, higher risk of whipsaws
Less sensitive to price movements, lower risk of whipsaws

EMAs and SMAs have advantages and disadvantages, and the choice of which to use ultimately depends on the trader's trading style, risk tolerance, and market conditions. Some traders prefer to combine both EMAs and SMAs to balance their strengths and weaknesses.