Below we have listed a number of indicators used in technical analysis that are available in the MetaTrader trading platform.
Average Directional Movement
One of the most common technical tools used to determine a market trend (i.e. the tendency of the financial asset’s price to move in a particular direction). This indicator was described in full detail by Welles Wilder in his book New Concepts in Technical Trading Systems.
Bollinger Bands
Bollinger Bands (also called standard deviation channels) represent lines (bands) plotted at levels equal to a certain amount of standard deviation from a moving average curve on a price chart. The width of standard deviation depends on market volatility. Bands widen in more turbulent market conditions and narrow during more stable periods.
Commodity Channel Index
This technical indicator is used to measure deviations of an asset’s price from its statistical historical average. When the index is high, the price is considered to be overvalued (unusually high) compared to its average. A low reading means that the price is undervalued (unusually low) compared to its average.
DeMarker
This oscillator reflects the relationship between the current price and the previous price bar. If the current high is above the previous high, the difference is calculated and recorded. If the current high is below or equal to the previous high, then the difference is either negative or equal, so the indicator is set to zero. The calculation is repeated over a series of consecutive days, and the sum of these values makes up the numerator of the DeMarker equation. The denominator is the numerator value plus the difference between price lows of the current and previous bars. A reading below 30 indicates a potential reversal to the upside; any value above 70 points means that price may reverse to the downside.
Envelope
This technical indicator is composed of two moving average lines. One of the lines is shifted upwards; and the other, downwards. When the market moves beyond the limits of a trading range as a result of active sell-offs or purchases, the trend is most likely to reverse.
Moving Average
This tool has gained widespread recognition among technical analysts. MAs may be either used on their own or form the basis for other, more complex, trading indicators. Moving averages are measured over a predefined time period. Longer time frames reduce the probability of false signals but at the same time weaken the sensitivity of an MA to price data.
MACD
The MACD is an oscillator reflecting the difference between two exponential moving averages (EMAs) of closing prices. It is commonly calculated by subtracting a 26-day EMA from a 12-day EMA. However, the function actually uses exponential constants of 0.075 and 0.15, which are closer to 25.6667 and 12.3333 periods. A 9-period EMA of the MACD line is often used as a signal line on the MACD histogram.
Momentum
This technical indicator measures the rate of an asset’s price fluctuations for a given period of time rather than prices themselves.
Oscillator
In general, an oscillator is calculated as a difference between a shorter-term moving average and a longer-term MA.
Parabolic SAR
The Parabolic SAR is an indicator plotted on a price chart that is similar to a moving average. The SAR stands for Stop and Reverse as this tool is used to identify points of potential trend stops and reversals. Unlike MAs, the Parabolic SAR moves with higher acceleration (referred to as the Acceleration Factor) and may change its position relative to prices. If the price breaks through the Parabolic SAR lines, the indicator signals a potential stop or reversal of a trend. In this case, further SAR values will be placed on the opposite side of price action. When a reversal takes place, the highest or lowest price over the previous period will act as a reference point. Such a reversal indicates either the end of a trend (i.e. an asset starts correcting or trading sideways) or its reversal.
Rate of Change
One of the most effective and simple oscillators that reflects the percentage change in price from one period to the next. The Rate of Change is measured by comparing the current price with the price n periods ago. Such periods can range from one minute to one month.
Relative Strength Index
The RSI is a technical indicator measuring the strength and speed of price changes. This oscillator is based on closing prices as it compares the average upward and downward price movements over a specified time period.
Standard Deviation
This indicator shows the degree of variation between the actual price and its average value over a certain time period. The Standard Deviation is calculated as the average square root of price deviation from its moving average.
Stohastic Oscillator
This tool compares the current closing price with the price range for a predefined period of time. The Stochastic Oscillator consists of two separate lines.
William's Percent Range
This is a dynamic indicator that determines overbought and oversold conditions. It represents a single line plotted on an upside-down scale.
The most sophisticated chartists can benefit from the opportunity to export MetaTrader data to specialized trading systems such as Omega TradeStation and MetaStock for more detailed technical analysis.
Below we will describe several basic trend-following indicators in more detail.
The moving average (MA) is the most frequently used indicator in technical analysis. Moving average lines are added directly to the chart reflecting price movements. A moving average is calculated over a certain time period selected by a trader. The shorter this period is, the higher the probability of getting false signals is. At the same time, longer periods imply a weaker sensitivity of the moving average.
Moving averages belong to the category of analytical tools following the trend. They are intended to signal a potential trend reversal and spot the beginning of a new trend and the end of an existing one. Therefore, MAs track the process of trend development. They can be considered curved trend lines. However, a moving average is unable to forecast price shifts in the same way as graphical analysis can predict market dynamics. Instead of running ahead of price movements, it follows behind their dynamics over time. MAs can only indicate the formation of a new trend after (not before) it actually emerged.
Building a moving average is an effective technique for spotting and measuring trends by smoothing price values.
Indeed, after higher and lower price deviations have been smoothed out to average values thus filtering out the noise from random fluctuations and flattening the curve, it is much easier for a chartist to monitor the development of present market trends.
A short-term moving average provides more accurate results in tracking price movements than long-term MAs. Time lags can be reduced through the use of shorter time frames but still cannot be eliminated completely. Short-term moving averages work best in a sideways market. Longer-term MAs are preferred in a trending (bullish or bearish) market as they are less sensitive.
Simple moving average
A simple (arithmetic) moving average (SMA) is calculated as follows:
where Рi is the closing prices of day i, and n is the period.
This type of moving averages is widely used by most technical analysts. However, some chartists are skeptical about it, citing two main reasons to doubt the efficiency of SMAs.
First, SMA analysis only takes into account the data contained within the period covered by an SMA.
Second, a simple moving average assigns equal weight to each day’s price values. For example, in a 10-day moving average the price from the first day (10 days ago) carries the same weight (10%) as the price from the last day (yesterday), as well as all the other days’ prices. Similarly, a 5-day moving average implies that the average weight of each day’s price equals 20%.
Meanwhile, some experts argue that more weight should be attributed to more recent price data. This probably makes sense because it takes longer for a simple moving average to signal a reversal whenever a new trend emerges than in the case of the weighted moving average, which we will discuss below.
Weighted moving average
Some technicians use weighted moving averages (WMA) to solve the problems related to average day values.
The following formula is used to calculate the WMA:
where Wi is the weight of component i (price).
The weight assigned to prices in the formula above can be selected by a trader depending on the price dynamic of the asset being traded. There are several techniques for smoothing out a series of prices including linear and exponential weighted moving averages. For example, in the case of a linear weighted moving average, Wi (weight) equals i (price).
Exponential moving average
The exponential moving average (EMA) has a more complex structure than the WMA or SMA, making it harder to calculate. It allows a chartist to fix the two weaknesses of a simple moving average.
First, the EMA assigns more significance to recent days’ prices. That is why it is also called exponentially weighted. Even though previous price dynamics has smaller weight, all of the price data is used to calculate an exponential moving average. In this case, the formula looks somewhat more complicated:
EMAt = EMAt-1 + (k * (Pt - EMAt-1)),
where t is the present day, t-1 is the previous day, k equals 2 divided by (n + 1), and n is the period.
Even though the exponential moving average does not have the drawbacks of a simple MA, it is not the most efficient tool out of all the three types we have described. Below we will discuss the effectiveness of each MA type.
Average Directional Movement
One of the most common technical tools used to determine a market trend (i.e. the tendency of the financial asset’s price to move in a particular direction). This indicator was described in full detail by Welles Wilder in his book New Concepts in Technical Trading Systems.
Bollinger Bands
Bollinger Bands (also called standard deviation channels) represent lines (bands) plotted at levels equal to a certain amount of standard deviation from a moving average curve on a price chart. The width of standard deviation depends on market volatility. Bands widen in more turbulent market conditions and narrow during more stable periods.
Commodity Channel Index
This technical indicator is used to measure deviations of an asset’s price from its statistical historical average. When the index is high, the price is considered to be overvalued (unusually high) compared to its average. A low reading means that the price is undervalued (unusually low) compared to its average.
DeMarker
This oscillator reflects the relationship between the current price and the previous price bar. If the current high is above the previous high, the difference is calculated and recorded. If the current high is below or equal to the previous high, then the difference is either negative or equal, so the indicator is set to zero. The calculation is repeated over a series of consecutive days, and the sum of these values makes up the numerator of the DeMarker equation. The denominator is the numerator value plus the difference between price lows of the current and previous bars. A reading below 30 indicates a potential reversal to the upside; any value above 70 points means that price may reverse to the downside.
Envelope
This technical indicator is composed of two moving average lines. One of the lines is shifted upwards; and the other, downwards. When the market moves beyond the limits of a trading range as a result of active sell-offs or purchases, the trend is most likely to reverse.
Moving Average
This tool has gained widespread recognition among technical analysts. MAs may be either used on their own or form the basis for other, more complex, trading indicators. Moving averages are measured over a predefined time period. Longer time frames reduce the probability of false signals but at the same time weaken the sensitivity of an MA to price data.
MACD
The MACD is an oscillator reflecting the difference between two exponential moving averages (EMAs) of closing prices. It is commonly calculated by subtracting a 26-day EMA from a 12-day EMA. However, the function actually uses exponential constants of 0.075 and 0.15, which are closer to 25.6667 and 12.3333 periods. A 9-period EMA of the MACD line is often used as a signal line on the MACD histogram.
Momentum
This technical indicator measures the rate of an asset’s price fluctuations for a given period of time rather than prices themselves.
Oscillator
In general, an oscillator is calculated as a difference between a shorter-term moving average and a longer-term MA.
Parabolic SAR
The Parabolic SAR is an indicator plotted on a price chart that is similar to a moving average. The SAR stands for Stop and Reverse as this tool is used to identify points of potential trend stops and reversals. Unlike MAs, the Parabolic SAR moves with higher acceleration (referred to as the Acceleration Factor) and may change its position relative to prices. If the price breaks through the Parabolic SAR lines, the indicator signals a potential stop or reversal of a trend. In this case, further SAR values will be placed on the opposite side of price action. When a reversal takes place, the highest or lowest price over the previous period will act as a reference point. Such a reversal indicates either the end of a trend (i.e. an asset starts correcting or trading sideways) or its reversal.
Rate of Change
One of the most effective and simple oscillators that reflects the percentage change in price from one period to the next. The Rate of Change is measured by comparing the current price with the price n periods ago. Such periods can range from one minute to one month.
Relative Strength Index
The RSI is a technical indicator measuring the strength and speed of price changes. This oscillator is based on closing prices as it compares the average upward and downward price movements over a specified time period.
Standard Deviation
This indicator shows the degree of variation between the actual price and its average value over a certain time period. The Standard Deviation is calculated as the average square root of price deviation from its moving average.
Stohastic Oscillator
This tool compares the current closing price with the price range for a predefined period of time. The Stochastic Oscillator consists of two separate lines.
William's Percent Range
This is a dynamic indicator that determines overbought and oversold conditions. It represents a single line plotted on an upside-down scale.
The most sophisticated chartists can benefit from the opportunity to export MetaTrader data to specialized trading systems such as Omega TradeStation and MetaStock for more detailed technical analysis.
Below we will describe several basic trend-following indicators in more detail.
The moving average (MA) is the most frequently used indicator in technical analysis. Moving average lines are added directly to the chart reflecting price movements. A moving average is calculated over a certain time period selected by a trader. The shorter this period is, the higher the probability of getting false signals is. At the same time, longer periods imply a weaker sensitivity of the moving average.
Moving averages belong to the category of analytical tools following the trend. They are intended to signal a potential trend reversal and spot the beginning of a new trend and the end of an existing one. Therefore, MAs track the process of trend development. They can be considered curved trend lines. However, a moving average is unable to forecast price shifts in the same way as graphical analysis can predict market dynamics. Instead of running ahead of price movements, it follows behind their dynamics over time. MAs can only indicate the formation of a new trend after (not before) it actually emerged.
Building a moving average is an effective technique for spotting and measuring trends by smoothing price values.
Indeed, after higher and lower price deviations have been smoothed out to average values thus filtering out the noise from random fluctuations and flattening the curve, it is much easier for a chartist to monitor the development of present market trends.
A short-term moving average provides more accurate results in tracking price movements than long-term MAs. Time lags can be reduced through the use of shorter time frames but still cannot be eliminated completely. Short-term moving averages work best in a sideways market. Longer-term MAs are preferred in a trending (bullish or bearish) market as they are less sensitive.
Simple moving average
A simple (arithmetic) moving average (SMA) is calculated as follows:
where Рi is the closing prices of day i, and n is the period.
This type of moving averages is widely used by most technical analysts. However, some chartists are skeptical about it, citing two main reasons to doubt the efficiency of SMAs.
First, SMA analysis only takes into account the data contained within the period covered by an SMA.
Second, a simple moving average assigns equal weight to each day’s price values. For example, in a 10-day moving average the price from the first day (10 days ago) carries the same weight (10%) as the price from the last day (yesterday), as well as all the other days’ prices. Similarly, a 5-day moving average implies that the average weight of each day’s price equals 20%.
Meanwhile, some experts argue that more weight should be attributed to more recent price data. This probably makes sense because it takes longer for a simple moving average to signal a reversal whenever a new trend emerges than in the case of the weighted moving average, which we will discuss below.
Weighted moving average
Some technicians use weighted moving averages (WMA) to solve the problems related to average day values.
The following formula is used to calculate the WMA:
where Wi is the weight of component i (price).
The weight assigned to prices in the formula above can be selected by a trader depending on the price dynamic of the asset being traded. There are several techniques for smoothing out a series of prices including linear and exponential weighted moving averages. For example, in the case of a linear weighted moving average, Wi (weight) equals i (price).
Exponential moving average
The exponential moving average (EMA) has a more complex structure than the WMA or SMA, making it harder to calculate. It allows a chartist to fix the two weaknesses of a simple moving average.
First, the EMA assigns more significance to recent days’ prices. That is why it is also called exponentially weighted. Even though previous price dynamics has smaller weight, all of the price data is used to calculate an exponential moving average. In this case, the formula looks somewhat more complicated:
EMAt = EMAt-1 + (k * (Pt - EMAt-1)),
where t is the present day, t-1 is the previous day, k equals 2 divided by (n + 1), and n is the period.
Even though the exponential moving average does not have the drawbacks of a simple MA, it is not the most efficient tool out of all the three types we have described. Below we will discuss the effectiveness of each MA type.
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