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Technical Analysis: Definition, Examples & Strategies

Updated: Nov 1, 2022

Technical Analysis Definition

Technical analysis refers to investors finding common patterns in historical forex prices to improve their success in trading. These technical patterns help traders enter their trades, manage their risk, and potentially predict the future.

What Is Technical Analysis?

Technical analysis is a form of research that uses pattern recognition on historical price data in order to predict the financial markets. It is one of the most popular analysis tools amongst retail traders.

Technical analysis can be used on any piece of data as long as they have historical trading data, these consist of things such as stocks, futures, commodities, currencies and other securities.

This idea of technical analysis stems from the fact that traders feel like they can identify market patterns, which in turn will allow them to form an educated guess or prediction for the future price of that chosen stock or currency.

Technical Analysis Examples

What are the examples of technical analysis? Here are the top 8 most popular examples investors use:

  1. Moving Averages

  2. MACD (Moving Average Convergence Divergence)

  3. RSI (Relative Strength Index)

  4. Stochastic Oscillator

  5. Bollinger Bands

  6. Fibonacci Patterns

  7. Chart Patterns

  8. Candlestick Patterns

1. Moving Averages in Technical Analysis

The moving average is a lagging indicator that is used by traders to help identify and determine a trends direction, as well as its support and resistance levels.

Moving Averages On Daily Time Frame:

The moving average is a totally customisable tool which can be adjusted to preference by the trader, thus meaning that they can choose the time frame they want when calculating an average.

The most commonly used time periods for the moving average indicator are; 15, 20, 30, 50, 100 and 200 days.

One thing to note is that the longer the timeframe a trader uses, the greater the lag will be.

For example, I have shown that, a weekly moving average will have a significantly larger degree of lag to that of a daily moving average. This is because it contains price points for the past week compared to one day.

Moving Averages On Weekly Time Frame

In addition to this, the shorter the timeframe, the more price sensitive it will be to changes.

Whereas, longer time frames are less sensitive to price changes. Short term traders also tend to use short-term moving averages, in contrast long term traders tend to use longer term moving averages.

Types of Moving Averages

Simple Moving Average (SMA)

The SMA is calculated by taking the average closing prices of an asset over a certain period of time. Therefore, to calculate it the closing prices are divided by the number of periods.

For example, if you are using the 15-day moving average, there will be 15 different closing prices, so all you have to do is add them together and then divide by the number of periods (in this case it is 15).

SMA = A1 ​+ A2​ +… + An​​ / n


A= Average in period

n= Number of time periods​

Exponential Moving Averages (EMA)

The EMA places more weight on recent data points. The reason for this is because EMA’s react significantly to the most recent price changes.

When it comes to EMA’s the most popular time frames are the 12 and 26 day for short term averages. On the other hand, 50–200-day averages are the most popular EMA’s for long term trading.

“To calculate an EMA, you must first compute the simple moving average (SMA) over a particular time period.
Next, you must calculate the multiplier for weighting the EMA (referred to as the "smoothing factor"), which typically follows the formula: [2/ (selected time period + 1)]. So, for a 20-day moving average, the multiplier would be [2/ (20+1)] = 0.0952.
Then you use the smoothing factor combined with the previous EMA to arrive at the current value. The EMA thus gives a higher weighting to recent prices, while the SMA assigns equal weighting to all values.”

EMAt ​= [Vt​ × (s/1+d​)] + EMAy​ × [1−(s/1+d​)]


EMAt​=EMA today

Vt​=Value today

EMAy​=EMA yesterday

s= Smoothing

d=Number of days​

A good example of a moving average indicator is the Bollinger band indicator that I will discuss later on in this section.

Moving Averages Drawbacks

The main limitation of moving averages is that it is a lagging indicator. Therefore, it means that it is based and calculated from PAST data, hence meaning that it is not good at accounting for FUTURE changes in an assets price.

2. MACD (Moving Average Convergence Divergence) in Technical Analysis

The MACD is a trend following momentum indicator. The way in which the MACD is calculated is by subtracting the 26- period exponential moving average (EMA) from the 12- period EMA.

This shows the relationship between two different moving averages of a security’s price.

By identifying moving averages, the MACD can assist in indicating whether there may be a new bullish or bearish trend on the horizon.

After all, the trend is your friend! When it comes to visualising the MACD indicator, you will see three different numbers which are used for its settings.

- The first is the number of periods that are used to calculate the faster moving average

- Second is the number of periods that are used in the slower moving average

- Lastly, the third number is the number of bars that are used to calculate the moving average difference between the faster and slower.

In this example, you can see that the MACD limits are set to 12,26,9 (these are the default settings for most charting software).

- 12 represents moving average of previous 12 bars

- 26 portrays the moving average of previous 26 bars

- 9 signifies a moving average of the difference between the two moving averages mentioned above.

You will also notice that there are two lines on the MACD indicator, one is the MACD line and the second is the Signal line.

The MACD line is the difference between two moving averages, whilst the signal line indicates the moving average of the MACD line.

The MACD line is considered to be the ‘faster’ moving average, whereas, the signal line portrays the ‘slower’ moving average. From the example above, the slower moving average line would be a 9-period moving average.

What this indicates, is that we are taking the average of the last 9-periods of the ‘faster’ MACD line and now plotting it as our ‘slower’ moving average. The purpose of this signal line is to smoothen the sensitivity of the MACD line.

Alongside the MACD indicator, you will also notice a histogram. It is just a graphical representation of the difference between the MACD line and signal line. This may sometime give you an early sign that a crossover is about to take place.

Here you can see that, when the MACD line and signal line separate, the histogram gets larger. This is called the MACD divergence. The reason for this is because the MACD line moving away from the signal line, hence creating a divergence.

However, when the MACD line and signal line get closer to one another, the histogram will reduce in size. This is what is known as a convergence.

And voilà, this is how the Moving Average Convergence Divergence indicator got its name! Now that you know what the MACD indicator is, let me walk you through how you can trade using the MACD indicator.

How to trade using MACD

Before telling you how to trade using MACD, I wanted you to get a brief understanding of what it was.

Now you have that understanding, I will explain how you can use the MACD when trading, and why you may see it as a potentially viable indicator when choosing a trading strategy.

Firstly, what you need to know is that when a new trend appears, the MACD line (faster line) will react first and then begin to cross over the signal line (slower line).

This cross over is known to be called a ‘divergence’. What this indicates is that the current trend may be coming to an end, as well as indicating that a new reversal trend could be fashioned.

Here you can see that when the two lines cross over the histogram will temporarily disappear, this happens because at the time of the crossover the difference between the MACD line and the Signal line is 0.

When the trend reversal continues, the MACD line will diverge away from the Signal line, this causes the histogram to get larger. This is a good thing, as it gives a good indication of a strong trend.

MACD Drawbacks

The one most noticeable drawback of the MACD indicator is that it is a lagging indicator.

What this means is that a trend becomes apparent only after a large shift has already taken place. Thus, meaning that the MACD confirms long term trends, but cannot predict them.

3. Relative Strength Index (RSI) in Technical Analysis

When looking at the RSI, you can see that it has a range between zero and one hundred. Between those ranges it plots the recent price gain versus the recent price loss of an asset.

What this does is it then helps a trader gauge the momentum and strength of a trend.

Traders mainly tend to use the RSI as an indicator to identify when an asset is overbought or oversold. For example, when the RSI is 70 or above, the asset is considered to be overbought with the potential to decline.

On the other hand, when an assets RSI is 30 or below, the asset is deemed to be oversold, depicting that there could be a rally in the price of an asset.

My colleague Mark Wilson has a great article which solely goes over RSI, be sure to check it out!

RSI Being used in conjunction with candlestick patterns

RSI is not always the most accurate bit of tech that a trader can use. However, to optimise the RSI’s ability to tell you when an asset is overbought or oversold, traders can use other technical signals such as candlesticks to help them determine the strength of the trend.

In this example AUD/JPY's the trend is at a high and a bearish engulfing appears, the RSI being at 70 or above can tell you that the asset is being overbought. In this case RSI was at 73, after this AUD/JPY shorted and has never recovered to that price since.

This would have made a great short idea as long as you had done your fundamental analysis prior to looking at the charts. Remember that charts are used to time your trades!

RSI Divergences

When it comes to RSI divergences, it is not a hard concept to grasp, but it does sound confusing.

A bearish divergence in the RSI will be created when the RSI shapes an overbought reading that is followed by a higher high, this is corresponded on the assets price as a lower high.

What this indicates is that there is a rise in bearish momentum which could lead to a decline in the assets price. This is depicted by GBP/USD's price chart below.

Comparatively, a bullish divergence is created on the RSI as an oversold reading that is followed by a higher high, this is corresponded by the assets price which then makes a higher low.

This indicates to a trader that bulls are starting to gain momentum, potentially creating a trend reversal.

Traders must take into consideration that divergences in the RSI are rare when an asset is in a stable long-term trend. Ergo, using flexible overbought or oversold readings can help recognise more potential signals.


Divergence is one way to trade using RSI. In addition to that RSI swing rejection scan also be used.

This examines the RSI’s behaviour after it has emerged from an overbought or oversold area. Bullish wing rejection is composed of 4 parts:

1. RSI falls into oversold territory.

2. RSI crosses back above 30%.

3. RSI forms another dip without crossing back into oversold territory.

4. RSI then breaks its most recent high.

Now when looking for a bearish swing rejection, it is very similar to the bullish, but just the other way around. It is also comprised of four parts:

1. RSI rises into overbought territory.

2. RSI crosses back below 70%.

3. RSI forms another high without crossing back into overbought territory.

4. RSI then breaks its most recent low.

Difference between RSI and MACD

When it comes to the MACD and RSI, the MACD measures the relationship between two EMA’s, whilst the RSI measures a change in price correlated to recent highs and lows.

Both are used to measure the momentum of a certain asset. But you have to realise that they measure different factors, meaning that sometimes they give contradictory indications.

For example, the MACD could be indicating that buying momentum is still increasing for an asset, whereas RSI may be showing a reading that is at 70% or above (overbought).

With all this taken into consideration, both signals can be used to signal that there may be an upcoming change in the trend’s direction, this can come from the divergence, of which I have spoken about in this section previously.

Limitations of RSI

The main limitation of the RSI is that the indicator displays momentum. Therefore, an asset can stay overbought or oversold for a very long time.

Consequently, meaning that the RSI will be most useful where asset price is alternating between bullish and bearish movements.

4. Stochastic Oscillator in Technical Analysis

Akin to the RSI, a stochastic oscillator is another momentum indicator that compares a closing price of an asset to a range of that assets prices over a certain period of time.

Typically, 14-day periods are used when the stochastic oscillator is at work.

The reason it compares the closing price to prior price movements of an asset is because the indicator is attempting to predict price reversal points.

It is a two-line indicator that can be applied to any chart. It fluctuates between 0-100 and as I said before, it consists of 14 individual periods. To put this into perspective, on a weekly chart this will be 14 weeks and on an hourly it would be 14 hours.

Formula for the stochastic oscillator:

%K= (C-L14 /H14−L14C−L14) ×100

Where: C = The most recent closing price

L14 = The lowest price traded of the 14 previous trading sessions

H14 = The highest price traded during the same14-day period

%K = The current value of the stochastic indicator​

How to read the stochastic oscillator

The indicator Is scaled between 0-100, the general rule is that a score above 80 indicates that an asset is trading near the top of its high-low range (overbought).

On the other hand, a reading below 20 indicates that the asset is trading at the bottom of its high low range (oversold).

Non the less, when prices hit these levels it is not always indicative of an impending trend reversal. If the trend of an asset is strong, it can maintain in an overbought and oversold state for a long period of time.

Therefore, traders should take these changes and clues from the oscillator to look for potential trend shifts in the future.

Stochastic Oscillator Divergences

Just like the RSI, traders can look for divergences in the stochastic oscillator.

For example, if a bullish trend is nearing a higher high, but the oscillator prints out a lower high, it can be seen as a trend reversal where the bulls are exhausting their momentum and the bears are gaining momentum.

In this image below on AUDJPY, there is an example of a stochastic divergence. The trend has reached the top of an uptrend, there is a higher high being made.

In contrast the stochastic identifies a lower low. Thus hinting at a change in the prices direction. Lone behold, bears take over and AUD/JPY's price falls.

When combined with other indicators, the stochastic oscillator can help a trader identify support and resistance levels, as well as entry and exit points.

Difference between stochastic oscillator and RSI

Both the RSI and stochastic oscillator are momentum oscillators. However, they each have different theories and methods of how to use.

“The stochastic oscillator is predicted on the assumption that closing prices should close near the same direction as the current trend.”

“Meanwhile, the RSI tracks overbought and oversold levels by measuring the velocity of price movements.” – Investopedia

In other words, RSI is more useful during trending markets, whereas the stochastic oscillator is most effective in sideways or choppy markets.

Limitations of the stochastic oscillator

The primary limitation with the stochastic oscillator is that it can produce false signals when it is not used properly. This problem mainly arises when traders trade against the trend.

As I have said before, if the trend of an asset is strong, it can remain overbought or oversold for a long time.

5. Bollinger Bands in Technical Analysis

In this section I will only briefly be going over Bollinger bands, the reason for this is because my colleague has an article that is dedicated to explaining in depth what Bollinger bands are and how they are used.

Bollinger bands are a technical indicator that was developed by a man named John Bollinger. They are used to measure whether an asset is overbought or oversold.

It also indicates to use market volume. When the market is loud (prices increase or decrease dramatically), the bands expand as shown in the image below.

However, when the market is quiet what would you expect the bands top do? If you said correct then well done! Can you spot the difference?

The Bollinger bands consist of a central line and two price channels (bands) that are located above and below the central line. The centreline is the exponential moving average.

The two lines above and below the EMA represent the standard deviation for price above and below the EMA.

Standard deviation is just a mathematical formula that helps measure how spread-out numbers are.

One thing to note with Bollinger bands is that the price of an asset always returns to the middle of the bands. The upper line is seen as an area where price is overbought and the lower line is seen as the area where price is oversold.

The two lines above the EMA tend to act as dynamic support and resistance levels. The longer the timeframe you are in, the stronger these bands tend to be.

Avoid trading Bollinger bands when the bands are expanding, this usually means that price is not moving within a range but in a trend. Instead look for areas where the bands are stable or contracting.

This is when the bands squeeze together, this normally depicts that a breakout is about to occur.

“If the candles start to break out above the TOP band, then the move will usually continue to go UP.

If the candles start to break out below the BOTTOM band, then price will usually continue to go DOWN.”

Looking at the chart above, it is evident that the bands are squeezing together. The price has just started to break out at the bottom of the bands.

So, where do you think price will go?

If you said down, then well done! This is how the Bollinger squeeze tends to work. It is designed to help you catch a trend as early as possible.

Limitations of Bollinger Bands:

They are not a standalone trading system. They were created to give traders information in regards to the volatility of an assets price.

The creator John Bollinger has suggested that you should use two to three other indicators to provide more market signals. These include MACD and RSI.

6. Fibonacci Patterns in Technical Analysis

Fibonacci numbers are a technical indicator that are generated by mathematical sequences. It was developed by Leonardo Pisano Bigollo who was an Italian mathematician.

The most commonly used Fibonacci method is the Fibonacci retracement levels. The Fibonacci retracement levels are horizontal lines that help identify areas of support and resistance on an assets price chart.

Each level of the Fibonacci indicator is associated with as percentage. The percentage is how much of a prior move the price has retraced. The retracement levels sit at 23.6%, 38.2%, 61.8%, and 78.6%.

The way in which people use the Fibonacci retracements is when there’s a trend, the Fibonacci retracements can be used to help determine how deep a retracement could be.

There are two different types of waves, the first being impulse waves. These are larger waves in the trending direction. The second type of waves are the pullbacks, these are the smaller waves in-between.

The Fibonacci levels are mainly used to identify areas of support and resistance. The reason for this, is that if price is consolidating near those areas and then starts moving in a trending direction, a trader will enter a trade in the direction the trend is moving in.

For example, if there is an uptrend, you might wait for a retracement or pull back to buy the asset that is near an area of support within the Fibonacci levels.

On the other hand, if there is a downtrend, you would look to sell an asset when it retraces up to a key area of resistance that is identified by the Fibonacci levels.

Another effective way in which to use the Fibonacci levels are by also using other indicators in conjunction. A good indicator to use alongside the Fibonacci levels is the stochastic indicator.

Combining the two indicators allows traders to see oversold and overbought areas. In this strategy, it looks for key signals in the stochastic indicator when the price touches an important Fibonacci level.

If a trader sees these two things, it can be a strong signal to open a position.

Limitations of Fibonacci

One limitation is that Fibonacci levels are subjective, but this is like any technical indicator. In addition to this, another possible issue with the Fibonacci levels is that there are so many of them in the market.

Thus, meaning that price is bound to change direction near one of these areas.

This makes the indicator look effective in hindsight, but in real time it may be hard to identify which level will be significant.

7. Chart Patterns in Technical Analysis

Firstly, what are chart patterns? Chart patterns are the shape that a market will take based on its historical data. Chart patterns allow you to gain a potential idea of the possibility on which way a trend will continue or reverse.

It is important that you understand the idea of support and resistance when using chart patterns. This indicates price areas on a chart where a currency or stock may have been over brought or oversold.

Support is referring to the level at which an assets price stops falling and rises back up. Resistance is where the price usually stops rising and drops back down.

Think of support and resistance as supply and demand. When there are more buyers than sellers in the market (demand > sellers) the price tends to rise.

On the other hand, when there are more sellers than buyers in the market, price tends to fall (sellers > buyers).

To put this into perspective, when a woman sees a price of a designer handbag, she will be willing to pay a lot of money for that handbag because it looks nice.

However, there will always come a point where she realises that a handbag should never be worth that much (max consumer is willing to pay)

This is where her demand for that handbag will decrease. Here is a great example of what I was talking about before, the decrease in demand for the handbag ultimately becomes an area of resistance.

This is where the price of the handbag will start to fall towards a level of support as supply begins to outweigh demand.

Then, once the price of the handbag has fallen enough, women will tend to jump back into the market because the price is seen as ‘more acceptable’

However, if the increased buying continues, price will be driven up towards a further level of resistance from the past.

This occurs because demand will begin to increase relative of supply. Once a price breaks through a level of resistance, it may become a future level of support.

Now that I have explained what support and resistance are, I will be describing the 10 best chart patterns are, but first let me explain the different types of chart patterns.

Types of chart patterns

Chart patterns fall broadly into three categories: continuation patterns, reversal patterns and bilateral patterns.

A continuation signals that an ongoing trend will continue

Reversal chart patterns indicate that a trend may be about to change direction

Bilateral chart patterns let traders know that the price could move either way – meaning the market is highly volatile”

You’ve made it this far into the article, here I will be depicting what I find to be the top 10 best chart patterns out there for you to use.

Top 10 best chart patterns in Technical Analysis

1. Head and shoulders

The head and shoulder chart patterns are formed when a security’s price rises to a peak (shoulder), falls back down to the base of the prior move, rises again to form the largest peak (head), price then retreats again to the original base, rises again, but only to the peak of the first initial peak (shoulder)