IC Markets

Moving Averages: The Cornerstones of Technical Indicators

In the previous part of our series introducing indicators, we have already mentioned in general what moving averages can be used for. Now, we will take a closer look at their various types, what they indicate and how we can utilize them during technical analysis.

In Forex trading, the moving average is a widely used technical indicator that helps traders monitor market momentum and trend. There are three main types of moving averages - the Simple Moving Average (SMA), Exponential Moving Average (EMA), and the Weighted Moving Average (WMA). The SMA calculates the average closing prices over a specified time period, providing a smooth line on the chart that helps reduce the noise of price fluctuations and identify long-term trends. On the other hand, the EMA and WMA give more weighting to recent data points, with the EMA being more suited for those who trade based on short-term volatility, while the WMA can provide a more accurate reflection of market trends.

Simple Moving Average (SMA)

The simple moving average is the most basic type of moving average, which we may have encountered in statistics before. Its calculation involves summing up the closing prices over a certain number of time periods and then dividing this sum by the number of periods, resulting in each closing price having equal weight. The chosen time period is usually a trading day, meaning the moving average is calculated from the average of daily closing prices. However, these time periods can be longer or shorter, depending on which chart the moving average is applied to. The resulting value is the simple moving average, which is primarily useful for smoothing out short-term price fluctuations and identifying support and resistance levels. The average is calculated using the following formula, where n is the number of periods examined, and price represents the closing price.

SMA = (P1 + P2 + P3 + ... + Pn)

Exponential Moving Average (EMA)

The exponential moving average is similar to the simple moving average but places greater weight on the most recent price movements, which it achieves through a different formula. The exponential moving average is calculated by taking the difference between the current price and the previous exponential moving average, multiplying it by a smoothing factor, and adding the product to the previous exponential moving average. The smoothing factor is composed as follows: 2/(n+1), where n is the number of periods under consideration. As recent price movements are given more weight in the moving average, it may be more suitable for identifying trend reversals. The exponential moving average is calculated using the following formula:

EMA = (PriceCurrent - EMAprev) × (2 / (n + 1)) + EMAprev

As you may have noticed, the EMA formula requires the previous EMA value to calculate the current EMA.
But how to get the first EMA?

To get the very first EMA, you can use a simple moving average (SMA) of the initial set of data points as a starting point. For example, if you are calculating a 10-period EMA, you can first calculate the 10-period SMA using the initial 10 data points. This SMA value will be used as the initial EMA value. From there, you can continue using the EMA formula to calculate subsequent EMA values.

So the formula for the above example is the following:

First EMA = (P1 + P2 + P3 + ... + P10)

Weighted Moving Average (WMA)

We may come across it less often, but the weighted moving average also places greater emphasis on recent price movements, similar to the exponential moving average. The calculation of the moving average is done by multiplying each price by its own weighting factor and then dividing the sum of weighted prices by the sum of weighting factors. The formula is as follows, where n is the number of periods under consideration:

At first, the formula may seem complicated, but for example, for a 5-day period, it simply means that the most recent closing price has a weight of 5/15, and the next one has a lower weight of 4/15, and so on until the fifth closing price, which only has a weight of 1/15 in the average. The weighted moving average assigns greater weight to more recent data points than to more distant ones, making it more suitable for identifying trends and possible trend reversals.

WMA = (P1 × 1 + P2 × 2 + P3 × 3 + ... + Pn × n)
(1 + 2 + 3 + ... + n)

What can we use these averages for?

We can use these moving averages in various ways during our technical analysis. Firstly, they can be applied to identify short-term and long-term trends, as they smooth out the shorter fluctuations, making it clearer for investors to see in which direction the price is moving.

The degree to which the moving average smoothes out the chart can vary depending on the time period used for the calculation. A moving average can be 20, 50, or even 200 days long, just to mention the most commonly used periods, but for a weekly chart, we can display 50 or 200-week moving averages. Since moving averages are calculated from past data, they usually signal a trend reversal with a delay, so they may not be the best tools for identifying short-term trend changes.

Golden cross, Death cross

It may be worth displaying multiple moving averages on a chart with different time periods simultaneously. This is because the relationship between moving averages can also be observed and used to interpret the technical picture. Typically, the 50-day and 200-day moving averages are shown together, and conclusions are drawn from their relative positions. If the 50-day moving average is above the 200-day moving average, this usually indicates an upward trend, and the reverse is also true, i.e., if the 50-day average occupies the lower position, a downward trend characterizes the movement of the price.

This shows that changes in the relative position of moving averages can be important to observe, which is why the intersection of the two moving averages often receives special attention in interpreting the technical picture. If the 50-day moving average crosses the 200-day moving average from below, we can talk about the appearance of a golden cross, which typically indicates the start of an upward trend. Conversely, if the 50-day moving average crosses the 200-day moving average from above, it may indicate the end of an upward or sideways trend and the beginning of a downward trend, commonly known as the death cross. The chart below shows first the death cross and then the golden cross on the daily chart of the S&P 500 index:

Supports, Resistances

However, we can use moving averages not only to identify trends or trend reversals, but also to mark resistance or support levels. In many cases, it is actually the moving averages that halt upward or downward movements of the price. It is important to note that these resistance or support levels do not necessarily mean that the price will stop there, but they can facilitate the identification of breakouts or breakdowns.

In addition to the above, moving averages can also be used to calculate other indicators, such as the Moving Average Convergence Divergence (MACD), as the name suggests, the basis of which is also formed by moving averages. However, we will discuss this in more detail in our next analysis.

In summary, it can be said that moving averages are almost inevitable in technical analysis, whether it is about identifying trends or resistance and support levels, and many indicators are also based on moving averages, so it can't hurt to understand how they are calculated.

Applying the Moving Average Crossover Strategy in Forex Trading

A common trading strategy among both beginner and seasoned traders is the moving average crossover. This occurs when a short-term EMA or WMA crosses above or below a longer-term SMA. A bullish breakout happens when the short-term average moves above the long-term average, suggesting a good time to buy. Conversely, a bearish breakout occurs when the short-term average falls below the long-term average, indicating it might be suitable to sell.

This technique aligns with market conditions and assists in adjusting trading decisions based on price fluctuations. However, like any technical indicator, it isn't foolproof and doesn't guarantee protection from loss. Ultimately, the effective use of moving averages depends on the trader's understanding of the calculations, the chosen time frame, and their ability to interpret the chart correctly.


Q: What is a moving average in trading?
A: A moving average is a statistical tool used by technical analysts to smooth out short-term fluctuations and identify the underlying trend in a security's price. It's calculated by taking the average of a currency or asset's prices over a specified time, which could be short-term or long-term.

Q: How can using a moving average help in trading?
A: A moving average helps filter out random price movements, providing a clearer view of the overall trend. This can give traders a better understanding of the price action and offer a solid foundation for making trading decisions.

Q: What's the difference between a simple moving average and a weighted moving average?
A: A simple moving average (SMA) gives equal weighting to all values, while a weighted moving average (WMA) gives more weight to more recent data. This makes WMAs more responsive to recent changes in price.

Q: What is a golden cross in moving averages?
A: A golden cross occurs when a short-term moving average crosses above a long-term moving average, implying an upward trend. This can be an indication to buy and is one of the various applications of moving averages.

Q: What do I need to know to fully understand moving averages?
A: To fully understand moving averages, you need to know different ways to calculate them (like using arithmetic or weighted averages), understand what they indicate (such as upward or downward trends), and know how to apply them on a graph. Remember, while versatile, they're not a standalone recommendation but should be used alongside other long-term indicators.

Q: Can moving averages be used for different timeframes?
A: Yes, moving averages can be adjusted to suit various timeframes. For instance, traders might use a 200-day moving average for a long-term perspective, while a 50-day moving average could be used to identify more recent trends.

Q: How can I leverage moving averages in my trading strategy?
A: Moving averages can be used to help identify buy and sell signals. For example, when the price of an asset moves above its moving average, it could be a signal to buy. Conversely, if it drops below the moving average, it could signal a selling opportunity. However, these signals should be used in conjunction with other technical analysis tools to validate them.

Q: What is the importance of the number of periods in calculating moving averages?
A: The number of periods used in calculating a moving average plays a crucial role in defining the sensitivity of the indicator. Short-term moving averages with fewer periods are more sensitive to price changes and can quickly reflect recent data. Conversely, long-term moving averages with more periods are less sensitive and can provide a clearer image of the overall trend.

Q: How does a moving average help with the analysis of price action?
A: A moving average helps smooth out random price fluctuations, providing a clearer picture of the overall trend in price action. This can be particularly useful for identifying patterns in the market and making informed trading decisions.

Q: What is the meaning of a 'moving' average?
A: The term "moving" refers to how the average is calculated over a specified time period. With each new value or data point, the earliest one is dropped, and the average is recalculated or "moved."

Q: How is a moving average used to construe trends in the market?
A: Moving averages help construe market trends by smoothing out price fluctuations and highlighting the direction of the overall trend. For instance, if a security's price is consistently above a moving average, it suggests an upward trend. Conversely, if the price is continually below the moving average, it indicates a downward trend.

Q: How does the Weighted Moving Average (WMA) differ from the Simple Moving Average (SMA)?
A: The primary difference between WMA and SMA lies in their sensitivity to recent price changes. The WMA gives more weight to recent data, making it more responsive to new changes in price. On the other hand, SMA assigns equal weighting to all data points, making it less sensitive to recent price fluctuations.