Technical Indicators Defined & Explained

A guide to understanding and applying the most popular technical indicators

by BDSwiss Trading Academy

Any information appearing on this graph or text is based solely on reasonable assumptions and does not December 2020 represent a reliable indication of future performance, nor does it represent a recommendation for trading decisions. Index Page

01 RSI - Relative Strength Index 03

02 Average Directional Index 07 03 Parabolic SAR 10 04 Moving Average Convergence and Divergence MACD 13 05 Bollinger Bands® 16 06 Linearly Weighted Moving Average 19 07 Exponential Moving Average 22 08 Simple Moving Average 25 09 Stochastic Oscillator 28

RSI Relative Strength Index

• RSI was developed in 1978 by J. Welles Wilder Jr. • It is among the most widely used trading indicators in technical analysis. • RSI is a momentum indicator, which means it helps measure the velocity of a particular assets price changes. • In its initial form, the RSI was designed for stock trading. As it started proving efficient, traders began applying it to other assets as well.

The Relative Strength Index is an indicator that helps traders capture market momentum by measuring the magnitude of price fluctuations. Traders use RSI to recognize oversold and overbought markets and decide on when to open a position.

The RSI takes the form of a line between two extremes (also known as an “oscillator”). It can have a value between 0 and 100.

The RSI is estimated on the scale from 0 to 100. The traditional interpretation of the Relative Strength Index supposes that anything above the value of 70 indicates that the given asset is overvalued and the market is overbought. On the contrary – assets with RSI below 30 are considered undervalued and their market – oversold.

Once we use the RSI to identify an oversold or an overbought asset, then we can expect a trend reversal or a correction and capitalize on it.

Oversold signals suggest that the selling pressure in the given asset is easing, and the traders should brace themselves for a potential rebound.

Overbought signals, on the contrary, indicate the momentum when the asset is reaching its maximum levels for bulls and could soon experience a correction.

Buy Signals

The Bullish Oversold Signal is a trend reversal signal that occurs in situations where the RSI falls below 30% and bounces back. There is no difference in how low it will go. The important thing here is for it to rise again above the 30% mark. Once it does, it is an indication that bulls are taking over, and a new upwards trend may be forming.

The Bullish Divergence Signal is another trend reversal signal that occurs when the RSI and the price divert from each other. This happens when the price makes a lower low while the RSI marks a higher low. Depending on the number of times this event repeats, this could indicate the strength of the forming signal (the more, the better for the bulls). This comes to show that it is imperative to look at both – the RSI and the price movement.

Sell Signals

The Bearish Overbought Signal indicates when a trend reversal may take place. To spot such an indication, make sure to look for situations where the RSI surpasses the 70% mark and then falls back below it. This could indicate that the bears are getting stronger, and a trend reversal is about to take place soon.

The Bearish Divergence Signal is observed when the RSI marks a lower high, and the price marks a higher high. Once again, the more repetitive this process is, the stronger the upcoming bearish signal will be. This is another trend reversal signal that confirms the importance of taking into account both the RSI and the price movements and not analyzing any of them in isolation.

The relative strength index (RSI) is computed with a two-part calculation, starting with the below formula:

The average gain and loss used in the calculation is the average percentage gain and loss during a pre defined period, using a positive value for the average loss. As a standard 14 periods are used to calculate the initial RSI value. For example, imagine the market closed higher seven out of the past 14 days with an average gain of 1%. The remaining seven days all closed lower with an average loss of -0.8%. The calculation for the first part of the RSI would look like the following expanded calculation:

Once there are 14 periods of data available, the second part of the RSI formula can be calculated. The second step of the calculation smooths the results.

Using the formulas above, RSI can be calculated, where the RSI line can then be plotted beneath an asset’s price chart.

The RSI will rise as the number and size of positive closes increase, and it will fall as the number and size of losses increase. The second part of the calculation smooths the result, so the RSI will only near 100 or 0 in a strongly trending market.

Average Directional Index

• The Parabolic SAR is a technical analysis tool developed by J. Welles Wilder Jr., the creator of the RSI. • The ADX is a trend indicator and is shown as an oscillator in a window below the pricing chart. • Despite its name, this indicator doesn’t give you any information about trend direction. It will show the strength of the trend.

As with many trend indicators, ADX lags behind the price, so is not useful if you want to get in on trends early. But it is useful if you only want to trade strong trends.

Combined with a directional trend indicator, such as Parabolic SAR, ADX can confirm that a trend is strong and is going to continue. This should give you more confidence when entering into a position.

When showing a between 0-25, this usually signals a weak trend, when the readings are between 25 and 50, this shows a strong trend, any readings above 50 indicates a very strong trend.

The ADX oscillator’s values are calculated automatically using the following formula:

ADXi = EMAi x ( | DMI ( + ) - DMI ( - ) | / ( DMI ( + ) + DMI ( - ) ) x 100

ADXi is the Average Directional Index value of the period being calculated.

EMAi is the Exponential Moving Average value of the period being calculated. For more information.

DMI(+) is the positive Directional Movement Index value of the period being calculated. For more information.

DMI(-) is the negative Directional Movement Index value of the period being calculated.

Parabolic SAR

• The Parabolic SAR is a technical analysis tool developed by J. Welles Wilder Jr., the creator of the RSI. • They are used to determine the price direction of an asset. It also draws attention to when the price direction is changing. • The Parabolic SAR is also referred to as the Stop and Reversal system.

The Parabolic SAR is a trend indicator. Dots are placed on the chart either above or below the price, as they indicate the potential direction of the price movement.

When the dots are above the current price, this indicates that the market is in a downtrend. Traders can use this to short or sell. When the dots are below the price, the market is in an uptrend, indicating that you should go long or buy.

Any information appearing on this graph or text is based solely on reasonable assumptions and does not represent a reliable indication of future performance, nor does it represent a recommendation for trading decisions. 11 The Parabolic SAR should not be used in a ranging market. When the markets are moving sideways there will be lots of noise and this will make the dots flip from one side to the other providing no clear trading or false signals.

The indicator can be used to gauge the direction of the asset and be used for placing stop-loss orders and is used by traders who want to catch high-momentum moves.

Some good indicators to use alongside the Parabolic SAR are Moving Averages, Stochastic and the Average Directional Index (ADX).

Parabolic SAR calculation

The Parabolic SAR indicator uses the most recent extreme price (shown as EP below) along with an acceleration factor (shown as AF) to determine where the indicator dots will appear.

The Parabolic SAR is calculated as follows:

Uptrend: PSAR = Prior PSAR + Prior AF (Prior EP - Prior PSAR)

Downtrend: PSAR = Prior PSAR - Prior AF (Prior PSAR - Prior EP)

Where:

EP = Highest high for an uptrend and lowest low for a downtrend, updated each time a new EP is reached.

AF = Default of 0.02, increasing by 0.02 each time a new EP is reached, with a maximum of 0.20.

• Invented by Gerald Appel in 1979 and still widely used to this day by many traders worldwide. • Moving Average Convergence Divergence is a trend-following momentum indicator. That shows the relationship between two moving averages of an asset. • The MACD is calculated by subtracting the 26-period Exponential Moving Average from the 12-period EMA. • The Signal line is represented by a 9-day period EMA.

The MACD on the MT4 platform shows the difference between 26-period and 12-period EMA, this is expressed as a Histogram. To find buying or selling signals a 9-period moving average is also added and we look for crossovers to signal buying or selling decisions.

The basic rule here is that when the MACD falls below the signal line this indicates a sell and when the MACD goes above the signal line this indicates a buy signal.

Any information appearing on this graph or text is based solely on reasonable assumptions and does not represent a reliable indication of future performance, nor does it represent a recommendation for trading decisions. 14 When there are clear instances of divergence. For example, when the MACD is making new highs and prices are falling to reach new highs this can be a signal that the current bullish trend may be nearing an end. A bearish divergence would be when the MACD is making new lows and prices are not reaching new lows. In these cases, the divergences are more significant when they occur at relatively oversold or overbought levels.

MACD calculation

When calculating the MACD, the value of a 26-period EMA is subtracted from a 12-period EMA. A 9-period SMA (the dotted signal line) is then plotted on top of the MACD.

MACD = EMA ( CLOSE, 12 ) - EMA ( CLOSE, 26 )

Signal = SMA ( MACD, 9 )

Where:

EMA – the Exponential Moving Average

SMA – the Simple Moving Average

Signal – the signal line of the indicator

• Bollinger Bands® are a technical analysis tool developed by John Bollinger in the early 1980s, for generating oversold or overbought signals. • Bollinger Bands® comprise of three lines, a Simple Moving Average with an upper and lower band set at a standard deviation. • Bollinger Bands® are a highly popular technique used by many traders.

A Bollinger Band® refers to a technical analysis tool. They are shown as a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of an assets price, but which can be adjusted to user preferences.

Calculated from a simple moving average, so older price data is weighed the same as the most recent prices, so new information may be diluted by outdated pricing data, this may be a concern for some traders. Also, some traders feel that the use of 20-day SMA and the 2 standard deviations may be a bit inconsistent and therefore will not work for everyone in every situation. Traders are able to adjust their SMA and standard deviation accordingly and monitor them should they wish.

The central concept of Bollinger Bands is when the bands come close together like they are constricting the moving average. This is referred to as ‘The Squeeze’. This signals a period of low volatility and a possible sign of future volatility, a possible trading opportunity.

Any information appearing on this graph or text is based solely on reasonable assumptions and does not represent a reliable indication of future performance, nor does it represent a recommendation for trading decisions. 17 The wider apart the bands’ move may also signal that it is likely a decrease in volatility and the greater the change to exit a trade. These conditions are not trading signals as the bands give no indication when the change may happen or the direction the price will move in.

As with all indicators they are not meant to be a stand-alone trading system and John Bollinger himself suggested using them in conjunction with two or three non- correlated indicators that provide more direct market signals. Some of his preferred suggestions are MACD and RSI.

Bollinger Band® calculation

Here is this Bollinger Band® formula:

BOLU=MA(TP,n)+m∗σ[TP,n]

BOLD=MA(TP,n)−m∗σ[TP,n]

Where:

BOLU=Upper Bollinger Band

BOLD=Lower Bollinger Band

MA=Moving average

TP (typical price)=(High+Low+Close)÷3 n=Number of days in smoothing period (typically 20) m=Number of standard deviations (typically 2)

σ[TP,n]=Standard Deviation over last n periods of TP

• Also referred to a The Weighted Moving Average. This is one of the most popular and widely used indicators. • Developed to try and improve the SMA, by filtering out some of the market fluctuations by price values over the periods by adding extra weight to the average prices. • This allows the most recent prices to play a more important role in the calculation as all preceding ones diminish in a linearly.

The LWMA is used in the same way that you would use the SMA and EMA and is quicker to react to market pricing than both. The LWMA gives the trader a more crisp picture of the market behaviour to make informed trading decisions.

Any information appearing on this graph or text is based solely on reasonable assumptions and does not represent a reliable indication of future performance, nor does it represent a recommendation for trading decisions. 20 It works best on stable falling or rising markets and should be avoided in ranging or sideways markets.

As the LWMA uses historical data for its calculations it reveals the market trend that has already developed and will not show a future trend.

When added to a chart, a trader will now analyse the behaviour and try to predict where the beginning of a new trend will begin or the old trend will end. This is done by determining reversal points that can serve as trading signals similar to those of the indicator.

Linear Weighted Moving Average calculation

The LWMA indicator’s values are calculated using the following formula:

LWMAi = Sum / SumWeight

Sum = Pricei x N + Pricei-1 x (N-1) + .. + Pricei-N+1 x (1)

SumWeight = N + (N - 1) +.. x + 1 = N x (N + 1) / 2

Where:

LWMAi - the value of the current period that is being calculated.

Price - is the source (the Closing price or other) price of any period that is participating in the calculation.

N - the number of periods, over which the indicator is calculated.

• An exponential moving average is a type of moving average that places greater importance on the most recent price data. • The EMA also known as an exponentially weighted moving average, reacts more distinctly to recent price changes than a simple moving average, which applies an equal weight to all pricing data in the period set.

Any information appearing on this graph or text is based solely on reasonable assumptions and does not represent a reliable indication of future performance, nor does it represent a recommendation for trading decisions. 23 An EMA helps to reduce lag by applying more emphasis on recent prices and therefore they are more sensitive to recent prices.

A 12 day period and 26 day period EMA’s are most often the most quoted and analysed short-term averages. They are also both used for other indicators like the Percentage Price Oscillator (PPO) and the Moving Average Convergence Divergence (MACD).

As with all moving averages, an EMAs is better suited for trending markets. When the asset is in a strong and sustained uptrend, the EMA line will also show an uptrend and the opposite for a downtrend.

Exponential Moving Average calculation

While there are many possible choices in regards to the smoothing factor the most common choice is 2.

• The development of moving averages dates back to 1901 by the math historian Jeff Miller. However, it was only referred to as ‘Moving Average’ until sometime later. • The technique for smoothing data points was in use for decades before this came into use. • A moving average is referred to as a trend-following or lagging indicator, due to it being based on previous/past pricing information. The longer the time-period, the greater the lag.

It will help to smooth out price volatility and thereby making it easier to view the price of the asset. So when the SMA is pointing up, this generally means that the assets price is increasing and when pointing down the price is decreasing.

The SMA is customisable as we can select the number of time periods we want.

A popular method used for trading involves using a 50-day SMA and a 200-day SMA and when the two lines cross over each other, we either get a Death Cross or a Golden Cross. The death cross is when a 50-day SMA crosses below a 200-day SMA. This is generally seen as a bearish signal. A golden cross happens when a 50-day SMA crosses above a 200-day SMA, signalling a bullish turn.

Any information appearing on this graph or text is based solely on reasonable assumptions and does not represent a reliable indication of future performance, nor does it represent a recommendation for trading decisions. 26 A simple moving average is a technical indicator that can aid in determining if an asset price will continue or if it will reverse a bull or bear trend.

Many trader are unclear whether more emphasis should be placed on more recent pricing data. And feel that more recent pricing data better reflects the current assets trend. While other tend to think that by giving more significance to recent data will bias the trend.

While there is no correct time frame to use when setting up your moving averages, it is best to figure out which one works best for you by applying them to different time frames based on your preference.

Simple Moving Average calculation

An SMA calculates the average of a selected range of prices. The standard is to use the closing prices, by the number of periods in that range.

The formula used for calculating the simple moving average is as follows:

Where:

A = Average in period n n = Number of time periods

• The Stochastic Oscillator is a momentum indicator developed by George C. Lane in the 1950s. • The term Stochastic refers to the point of a current price in relation to its price range over a period of time.

The Stochastic Oscillator measures momentum by comparing the most recent closing price with the previous high/low trading range over a specific period of time.

The Stochastic Oscillator follows the speed and momentum of the price, not the price or volume of the underlying asset so, this means that it changes direction before the price itself and can therefore be considered a Leading Indicator as it uses a past price data to forecast future price movements in the market.

The Stochastic is used to identify the bullish and bearish divergences between the price and the indicator, which can anticipate upcoming price reversals and, as it oscillates within a range, it can also be used to identify overbought and oversold levels.

A divergence occurs when the price “diverges” from the indicator, i.e. the price makes higher highs while the indicator shows lower highs, or the price makes lower lows while the indicator shows higher lows.

The Stochastic is an oscillator which can range between 0 and 100 and any value above 80 is usually considered as overbought, while below 20 is considered oversold.

It is drawn on the chart window with 2 lines: the indicator line %K, and the trigger line %D.

An upward crossing of the %K-line through the %D line indicates that the current closing price is closer to the highest high of the specified time period of the indicator than it has been in the previous three sessions. This is considered a bullish signal, while the opposite is considered bearish.

Calculations:

The default setting for the Stochastic is 14 periods which means that the %K line uses the most recent closing price and the highest high and lowest low over the last 14 periods (if the timeframe is set to daily, the last 14 periods are equivalent to the last 14 days).

The %D line is a 3-period Simple Moving Average of the %K line.

The Stochastic Oscillator can be calculated using the following formula:

%K = (Most Recent Closing Price - Lowest Low) / (Highest High - Lowest Low) × 100

%D = 3-day SMA of %K

Lowest Low is the lowest price over the last N periods

Highest High is the highest price over the last N periods

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