A technical indicator uses a formula to generate data points. The data points are then used to create alerts, confirm other indicators or analyses, and forecast prices.
Technical overlays use the same scale as price, while technical indicators may be plotted independently.
Simple moving average (SMA)
A simple moving average is an arithmetic average of a set of data points where each data point is added together and then divided by the total number of data points. A simple moving average is a smoothing tool to display trends for a specific number of periods.
For example, a 50-period simple moving average finds the closing price of the last 50-periods, sums the 50 closing prices, and divides by 50 to calculate the average closing price of the previous 50 periods. New periods are then added to the calculation, while the oldest period is deleted from the calculation.
The simple moving average is typically plotted as a technical overlay.
Simple moving averages are used to determine price trends over a specific time horizon. 10, 50, and 200-day simple moving averages are often used as default indicators to define a security's short, medium, and long-term trend.
Simple moving averages can be used for short periods of time, such as the last 5 or 10 periods on an intraday chart, or long periods of time, such as 10 or 20 periods on a monthly or annual chart.
The length of the moving average determines the indicator’s responsiveness to new data points. The longer the moving average, the longer it takes for changes in the underlying security’s price to impact the moving average’s value. Similarly, the longer the moving average the less likely a single data point provides a false indicator of a change in trend.
Exponential moving average (EMA)
An exponential moving average is the weighted average of a set of data points where new data points receive greater weight in the average calculation.
An exponential moving average is a technical indicator of a trend that responds faster to new data points than a simple moving average because a multiplier is used to give preference to newer data points and reduce lag in responsiveness to price movements.
Exponential moving averages address the “drop-off effect” caused when the earliest data point rolls off of a simple moving average calculation. A number of technical indicators, such as the MACD, use exponential moving averages as a smoothing factor or signal line.
Multiple simple moving averages may be used simultaneously to determine levels of support and resistance, generate buy or sell signals, confirm trading signals, and more.
Moving average convergence/divergence (MACD)
The moving average convergence/divergence (MACD) is a technical indicator of momentum that uses moving averages to determine a trend’s strength. The MACD uses three exponential moving averages (a short term, a long term, and the average difference between the short and long term) to show price momentum.
The MACD indicates changes in trend direction, as well as overbought and oversold conditions, by showing the turning points where the signal line crosses over the other moving average lines.
The default parameters for most MACD calculations take the difference between a 12-period EMA and a 26-period EMA to create an oscillator around zero.
The “MACD line” is the difference between the 12 and 26-period EMAs, and the “signal line” is a nine-period EMA of the MACD line. The MACD line moves faster than the signal line because the signal line is an EMA of the MACD line.
MACD is known as a “centered-oscillator” because a cross above or below the zero centerline signals a change in momentum.
A positive MACD indicates upward momentum and means the average price of the last 12 periods is higher than the average price of the previous 26 periods. A negative MACD indicates downward momentum as the average price of the last 12 periods is lower than the average price of the last 26 periods.
The default 12, 26, and 9 settings of the MACD can be adjusted to create more or less signals from the indicator. Shorter values generate more signals, while longer values create less signals.
The MACD can be calculated on any timeframe from intraday, daily, weekly, or other data.
MACD values above zero are typically bullish and indicate an uptrend while MACD values below zero indicate a downtrend.
MACD is also used in mean-reversion systems to signal overbought or oversold conditions.
Peaks and troughs in the MACD lines are also compared to the price chart of the underlying security to determine convergence and divergence. Divergences between a price chart and the MACD mean the two are moving in opposite directions.
For example, if a security’s price makes a new high but MACD does not, then the two are diverging with MACD indicating decreasing momentum in the security’s upward movement. This divergence is a contrarian indicator.
The MACD may be displayed as a line chart or a histogram. The two display types relay the same information so traders select one or the other as a matter of preference.
A MACD histogram’s vertical bars above and below the zero centerline visually indicate positive and negative momentum. Crosses above and below the centerline represent the same information as positive and negative crosses of the signal line on a MACD line chart.
Relative strength index (RSI)
The relative strength index (RSI) is a technical indicator of momentum that measures the speed and change of price on a scale of 0 to 100, typically over the past 14 periods. Readings over 70 are considered overbought, while readings below 30 are considered oversold.
RSI measures the strength of a security’s price change by comparing up days and down days. When the sum of gains over a number of periods exceeds the sum of losses over the same period, RSI increases.
Because RSI is a bounded oscillator between 0 and 100, readings above 50 are normally consistent with securities in an uptrend.
Similar to the MACD, RSI is also used to confirm price action for a security. For example, if a stock makes a new high, but RSI fails to make a new high, there is a divergence between price and momentum.
Rate of change
Rate of change (ROC) is a technical indicator of momentum that measures the percentage change in price from period to period.
Rate of change is a relatively simple calculation that measures the amount a security’s price has changed over a defined period. ROC has a similar “drop-off effect” to the simple moving average because older data points are removed from the calculation and replaced with new data points.
There are several variations of the ROC calculation depending on the charting software used, but they all follow the same basic approach and have the same interpretation.
Positive ROCs indicate an uptrend and changes in the ROC’s direction (positive to negative or negative to positive) can also be used as a signal.
Rate of change is also referred to as “momentum” and is often used to confirm trends.
For example, when a security reaches a new high but the rate of change does not, there is a negative divergence between price and momentum.
The stochastic oscillator is a technical indicator of momentum that shows where the closing price for a period fits in the relative high-low range of a lookback period, typically 14 periods.
The stochastic oscillator expresses the closing price for a period as a percentage of the recent high and low for a security. The most recent closing price is the most important data point in the calculation.
The stochastic oscillator is plotted as two lines. The first line is the current stochastic oscillator percentage value, and the second line is a three-day simple moving average of the percentage value. These are known as %K and %D, respectively.
There are three varieties of stochastic oscillators: fast, slow, and full.
While similar to the relative strength index (RSI), the stochastic oscillator does not measure momentum and rates of change. Instead, it simply shows the price level relative to the security's recent trading range.
Stochastics are used as overbought and oversold signals, especially when a security is range bound.
Fast Stochastic Oscillator
The fast stochastic oscillator plots the traditional %K and %D lines. The fast stochastic compares the traditional raw stochastic number (%K) with a three-period simple moving average of that number (fast %D = 3-period simple moving average of %K).
Slow Stochastic Oscillator
The slow stochastic oscillator smooths %K by using a three-period simple moving average, meaning %K for the slow oscillator is the same value as %D for the fast oscillator. For the slow oscillator, %D is the three-period simple moving average of the new %K values. In other words, %D for the slow stochastic oscillator is the three-period simple moving average of the %D values from the fast stochastic oscillator.
Full Stochastic Oscillator
The full stochastic oscillator allows for customization. The trader specifies the number of periods for the smoothing of %K and for the calculation of %D.
The centerline of Bollinger bands is typically a 20-day simple moving average. The upper and lower bands are twice the 20-day standard deviation of price above and below the centerline.
Because the bands are drawn two standard deviations above and below the center simple moving average, approximately 95% of the security’s price action should occur within the bands.
The bands are dynamic and sensitive to changes in volatility. When the bands widen, price volatility is increasing. When the bands contract, volatility is decreasing.
Price tends to oscillate within the bands and the upper and lower bands are used as resistance and support, respectively. Breakouts above the upper band or below the lower band are often used as trading signals.
The Ichimoku cloud is a technical indicator that displays support, resistance, momentum, and trend in one chart overlay. Ichimoku clouds consolidate a number of indicators by using a variety of moving averages and other calculations to indicate areas of support and resistance on a price chart.
Five lines come together and form the “cloud” to identify support and resistance areas.
Various crossings of the five lines produce trading signals and are similar to moving average crossover systems. If the underlying price is above the cloud, the security is in an uptrend. If the underlying price is below the cloud, the security is in a downtrend.
Keltner channels are a chart overlay, volatility indicator that shows the upper and lower channels, or range, of price movement based on an exponential moving average and the average true range for the channel’s width.
Whereas Bollinger bands are based on standard deviation, Keltner channels are based on the average true range (ATR). The center line in a Keltner channel is typically a 20-period moving average while the upper and lower bands are often two times the average true range.
Pivot points are calculated using the prior period’s range to show potential support and resistance levels.
The prior day’s high, low, and closing price are used to calculate the pivot point, two levels of support, and two resistance levels. Pivot points were initially used by floor traders as a quick reference intraday.
Many traders use pivot points for intraday entry and exit points, as well as support and resistance levels for position scaling.
Pivot points may also be used as confirmation in conjunction with other signals. For example, an upward turn in a momentum indicator near a pivot point support level would be a bullish confirmation.
Because pivot points are based on the prior day’s closing price, they are a relatively sensitive indicator because new pivot point levels are calculated daily.
Volume-weighted average price (VWAP)
Volume-weighted average price (VWAP) combines price and volume to show where the average trading activity has taken place for a specified period. VWAP is calculated by dividing the total dollar value of all trades by the trading volume for the period referenced.
For example, intraday VWAP would take the total dollar value for all the trades for the current day and divide by the day’s trading volume.
VWAP is used to show both trend and demand for a security and is also used by institutions to assess the effectiveness of price execution for large orders.
VWAP is also used for support, resistance, entry, and exit levels as an alternative or complement to other moving averages because VWAP incorporates volume, while simple or exponential moving averages do not.
Average true range (ATR)
The average true range (ATR) is a technical indicator of volatility based on the average of a particular set of trading ranges over a defined number of periods.
The ATR is the average of the true range for a set of periods. The greatest of one of three ranges is calculated as the true range for a period: the current high minus the current low, the current high minus the previous period’s close, or the current low minus the previous close.
Once the true range is calculated, the average for a set lookback period is taken, typically 14 periods.
A decline in ATR indicates a decrease in recent volatility. An increase in ATR indicates an increase in recent volatility.
ATR is used in a number of ways, such as confirmation in breakout systems, with other indicators like Keltner channels, and in position sizing.
Chaikin money flow
The Chaikin money flow (CMF) is a technical indicator that uses price and volume to show the flow of funds into or out of a security by combining an accumulation and distribution indicator with an oscillator calculation.
Chaikin money flow is often used to confirm a price trend. If price is trending higher while the Chaikin money flow is also trending higher, CMF confirms the price action.
On balance volume (OBV)
On balance volume (OBV) is a technical indicator that uses price and volume to show the flow of funds into or out of a security. On balance volume is perhaps the best known volume-related indicator.
The day’s volume is adjusted for the change in direction (up or down) of price from the previous day and cumulated into the index.
For example, if today’s closing price is higher than yesterday’s closing price, then the total daily volume is added to the index. The index is a cumulative value of price and volume data.
OBV is interpreted in relation to a price trend: rising volume in one direction confirms the price trend.