Purpose, uses, formula and examples

What is a moving average (MA)?

In finance, a moving average (MA) is a stock indicator commonly used in technical analysis. The reason for calculating the moving average of a stock is to help smooth out the price data by creating a constantly updated average price.

By calculating the moving average, the impact of random, short-term fluctuations on the price of a share over a specified time frame is mitigated. Simple moving averages (SMAs) use a simple arithmetic average of prices over a period of time, while exponential moving averages (EMAs) place greater weight on more recent prices than older prices over the period.

Understanding a Moving Average (MA)

Moving averages are calculated to identify the trend direction of a stock or to determine its support and resistance levels. It is a trend-following or lagging indicator because it is based on past prices.

The longer the period for the moving average, the greater the lag. A 200-day moving average will have a much greater degree of lag than a 20-day MA because it contains prices for the past 200 days. 50-day and 200-day moving average figures are widely followed by investors and traders and are considered important trading signals.

Investors can choose different periods of different lengths to calculate moving averages based on their trading objectives. Shorter moving averages are typically used for short-term trading, while longer-term moving averages are more suitable for long-term investors.

Although it is impossible to predict the future movement of a particular stock, using technical analysis and research can help make better predictions. A rising moving average indicates that the security is in an uptrend, while a falling moving average indicates that it is in a downtrend.

Similarly, upward momentum is confirmed with a bullish crossover, which occurs when a short-term moving average crosses above a longer-term moving average. Conversely, downward momentum is confirmed with a bearish crossover, which occurs when a short-term moving average crosses below a longer-term moving average.

Types of moving averages

Simple moving average

A simple moving average (SMA), is calculated by taking the arithmetic mean of a given set of values ​​over a specified period of time. A set of numbers, or prices of shares, is added together and then divided by the number of prices in the set. The formula for calculating the simple moving average of a security is as follows:

SMA = A 1 + A 2 + … + A nn where: A = Average in period nn = Number of periods \begin{align} &SMA = \frac{ A_1 + A_2 + \dotso + A_n }{ n } \\ & \textbf {where:} \\ &A = \text{Average in period } n \\ &n = \text{Number of periods} \\ \end{align}

,SmA=aA1,+A2,+…+Aa,,where:A=Average in period aa=Number of periods,

Charting stock prices over 50 days using a simple moving average might look like this:

Exponential Moving Average (EMA)

The exponential moving average gives more weight to recent prices in an attempt to make them more responsive to new information. To calculate an EMA, the simple moving average (SMA) over a specified time period is first calculated.

Then calculate the multiplier for the weight of the EMA, known as the “smoothing factor”, which typically follows the formula: [2/(selected time period + 1)].

For a 20-day moving average, the multiplier would be [2/(20+1)]= 0.0952. The smoothing factor is combined with the previous EMA to arrive at the current value. Thus, the EMA gives a higher weight to recent prices, while the SMA assigns an equal weight to all values.

EMA t =

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where: EMA t = EMA today V t = Value today EMA y = EMA yesterday s = Smoothing d = Number of days \begin{aligned} &EMA_t = \left [ V_t \times \left ( \frac{ s }{ 1 + d } \right ) \right ] + EMA_y \time \left [ 1 – \left ( \frac { s }{ 1 + d} \right ) \right ] \\ &\textbf{true:}\\ &EMA_t = \text{EMA today} \\ &V_t = \text{Value today} \\ &EMA_y = \text{EMA yesterday} \\ &s = \text{Smoothing} \\ &d = \text{Number of days} \\ \end{align}

,EMAt,=[Vt​×(1+ds​)]+EMAy,x[1−(1+ds​)]where:EMAt,=EMA todayQt,=Value todayEMAy,=EMA yesterdays=Smoothingd=Number of days,

Simple Moving Average (SMA) vs. exponential moving average (EMA)

The calculation for EMA puts more emphasis on the recent data points. Because of this, EMA is considered a weighted average calculation.

In the figure below, the number of periods used in each average is 15, but the EMA reacts to the changing prices faster than the SMA. The EMA has a higher value when the price rises than the SMA and it falls faster than the SMA when the price falls. This reaction to price changes is the main reason why some traders prefer to use the EMA over the SMA.

Example of a moving average

The moving average is calculated differently depending on the type: SMA or EMA. Below we look at a simple moving average (SMA) of a security with the following closing prices over 15 days:

Week 1 (5 days): 20, 22, 24, 25, 23 Week 2 (5 days): 26, 28, 26, 29, 27 Week 3 (5 days): 28, 30, 27, 29, 28

A 10-day moving average will average the closing prices for the first 10 days as the first data point. The next data point will drop the earliest price, add the price on day 11 and take the average.

Example of a moving average indicator

A Bollinger Band® technical indicator has bands that are usually placed two standard deviations away from a simple moving average. Generally, a move to the upper band indicates that the asset is overbought, while a move near the lower band indicates that the asset is oversold. Since standard deviation is used as a statistical measure of volatility, this indicator adjusts itself to market conditions.

The Bottom Line

A moving average (MA) is a stock indicator commonly used in technical analysis, used to help smooth price data by creating a constantly updated average price. A rising moving average indicates that the security is in an uptrend, while a falling moving average indicates a downtrend. The exponential moving average is generally preferred over a simple moving average, as it gives more weight to recent prices and shows a clearer response to new information and trends.