When analyzing technical indicators, it’s important to remember that any single technical indicator on its own is not particularly telling.
You need context to understand what that technical indicator means. You can derive context by looking at information like a prevailing trend, chart pattern, and more. It’s like puzzle: it only makes sense when it’s all put together to create a coherent picture of the market.
Indicators can be categorized into overlays or oscillators:
Overlays: Overlays are indicators that use the same scale as the price and are plotted on top of the price chart.
Oscillators: Oscillators are displayed independently on a different scale below the price chart and will oscillate between a minimum and maximum value.
Certain technical indicators are considered leading indicators. A leading indicator has strong predictive qualities and can indicate the direction of the market before the price follows through. Leading indicators can be effective in signaling an imminent change in trend or momentum before the market begins to show that change. The best-known leading indicators include the Relative Strength Index (RSI), Stochastic Oscillator, and On Balance Volume (OBV).
Other technical indicators, meanwhile, are considered lagging indicators. Lagging indicators follow market trends. They indicate a shift in market trends, but they tend to lag behind that shift. Typically, a lagging indicator is used to confirm a trend after a trend has already begun to emerge. However, lagging indicators have less valuable in a volatile market with no clear trend. The two best-known lagging indicators are Bollinger bands and moving averages.
Moving averages are trend overlays that can indicate short, medium, and long-term trends. To calculate the moving average, we take the average price over a certain period of time. A moving average removes a lot of the ‘noise’ on the chart, including short-term volatility and price movements. It can make trends easier to spot.
There are two common ways to calculate moving averages, including simple moving averages and exponential moving averages. Both are considered lagging technical indicators.
A simple moving average (SMA) is just the sum of all closing prices over a particular time period divided by the number of periods. A 5-day SMA, for example, can be calculated by adding the closing prices for each day and dividing the sum by five. Over a longer time period, there’s greater lag. Longer scales smooth our price movements and tend to be less responsive than shorter time scales.
Exponential moving average (EMA), meanwhile, places greater weight on the most recent data points. This can ‘tighten’ the moving average to price movements, making the moving average more responsive to recent price movements.
Exponential moving averages use a weighting multiplier to give the most recent data points greater weight. This weighting multiplier can be calculated using the formula [2 / (Time Period + 1)]. In a 10-day EMA, the weighting given to the most recent price would be [2 / (10 + 1)] = 0.1818, or 18.18%.
There are also current exponential moving averages (EMAs), where you take today’s price x the weighting multiplier + yesterday’s EMA x (1 – weighting multiplier).
You don’t have to memorize these formulas. Charting tools apply these formulas automatically. However, it helps to know where these formulas are coming from.
Typically, the 200-day simple moving average (SMA) chart and the 50-day SMA chart are the two most popular scales for identifying medium to long-term trends. These two charts are also useful for identifying support and resistance levels, bullish and bearish crossovers, and divergences.
When the simple and exponential moving averages come together, it creates a crossover. This is considered a pivotal event that could signal a trend change.
The bullish crossovers, also known as golden crosses, occurs when the shorter scale moving average crosses above the longer scale moving average.
The bearish crossovers, also known as death crosses, occurs when the shorter scale moving average crosses below the longer scale moving average.
Meanwhile, if the current price crosses above the long-term moving average, it’s indicative of a bullish breakout. If the current price crosses below the long-term moving average, it indicates a bearish breakout.
HERE SOME PRECIOUS TIPS TO USE SMA and EMA:
Moving average convergence-divergence, or MACD, is a trend-following oscillator popular for gauging momentum. MACD takes two exponential moving averages (like the 12-day and 26-day EMA), then plots them against the zero lines to measure the momentum of a trend.
We also see the MACD histogram, which measures momentum based on the relationship between MACD and its signal line (the 9-day EMA of MACD).
A modern MACD oscillator indicator consists of four elements, including the MACD line, zero line, signal line, and MACD histogram:
Pivotal events include convergence, crossover, and divergence from the zero line and the signal line.
Relative strength index, or RSI, is a way to indicate momentum. Momentum can identify the strength of market trends, giving you a good idea of when to buy or sell based on whether markets are overbought or oversold.
RSI oscillates between 0 and 100, with the typical timeframe being 14 days. When RSI is below 30, it indicates the market is oversold. When the RSI is above 70, it indicates the market is overbought. However, some traders use 20 and 80 as the boundaries instead, which can be more telling for highly volatile markets (including crypto).
Because RSI is a leading indicator, the slope of the RSI can indicate a trend change before that trend is observed in the general market. For that reason, RSI is one of the most common ways of analyzing market conditions.
RSI = 100 – (100/1+RS)
In this formula, relative strength (RS) equals average gain over the average loss (RS = Average Gain/Average Loss).
A gain is a period where the price closes above the previous day’s closing, while a loss is a period where the price closes below the previous day’s closing. These values are absolute, which means that losses are calculated as positive values.
Although RSI divergences can be helpful, they’re only helpful within the appropriate context. As with other indicators here, it’s an important reminder to avoid using any single indicator as a signal without proper context.
You can see a bullish divergence when the price hits a lower low and RSI hits a higher low. A bearish divergence, meanwhile, occurs when the price hits a higher high and RSI hits a lower high.
We can also use RSI to observe RSI failure swings, which are seen as indications of potential trend reversals in a bearish or bullish direction.
A bullish failure swing occurs when RSI falls below 30, bounces past 30, falls back, but does not fall below 30 and makes a new high.
A bearish failure swing, meanwhile, occurs when the RSI breaks above 70, falls back, bounces without breaking 70, and falls back to a new low.
Average directional index (ADX) has risen in popularity in recent years to become a preferred indicator for estimating the strength of a trend. As a lagging oscillator, ADX offers little insight into the future trend direction, although it does indicate the magnitude of market forces behind a trend.
ADX oscillates between 0 and 100, with ADX typically below 20 in a ranging market and above 25 in a trending market. An ADX above 40 indicates a strong trend.
When calculating ADX, we need to determine the positive directional indicators (+DI) and negative directional indicators (-DI), which together create the directional movement indicator (DMI). We calculate DMI by collating the highs and lows of consecutive periods.
In this formula, +DM is the high for the current period minus the high for the previous period. -DM is the low of the previous period minus the low of the current period. The ‘smoothing’ part of the equation, meanwhile, involves taking the average of the last 13 periods, adding the most recent value, and then dividing the sum by 14.
ADX also takes into account average true range, or ATR, which indicates volatility. True range (TR) is the absolute value of the greatest among three price differences (the current period’s high minus the current period’s low, the current period’s high minus the previous period’s close, and the current period’s low minus the previous period’s close.
These formulas may seem complex. However, as mentioned above, you don’t need to memorize these formulas. There are plenty of tools that implement these formulas for you. If you want to be an informed technical trader, however, then it helps to understand where these formulas come from.
ATR offers no indication of trend direction. However, +DI and -DI do indicate trend direction. Traders can use ADX to determine the strength of the trend, then use crossovers of +DI and -DI to create signals that indicate potential reversals.
Let’s say, for example, the +DI line is crossing above or diverging upward from the -DI line with ADX above 40. This is a strong bullish signal. However, crossovers and divergences when ADX is below 20 are not signals of much consequence because there isn’t as much momentum behind these movements.
Bollinger bands trace their origin to American financial analyst John Bollinger, who developed the theory in the 1980s. Bollinger band analysis uses a moving average-based overlay to measure price volatility. The theory involves three bands, including a middle band to represent the simple moving average and an upper and lower band to represent standard deviations.
For the middle band, analysts typically use the 20-day simple moving average (SMA). The upper band, meanwhile, is the same SMA with two standards of deviation added, while the lower band subtracts two standards of deviation. Analysts can adjust the number of periods based on their trading preferences. However, analysts will use the same number of periods to calculate SMA that they use to calculate standard deviation.
The width of the Bollinger bands indicates volatility.
Approximately 90% of price movements occur within the Bollinger bands. When the price suddenly moves outside of the upper or lower band, it indicates a breakout could be upcoming.
During a strong uptrend in markets, prices tend to hug or move out of the upper band, for example, while during a strong downtrend, price activity is focused around the lower band. During market swings, the middle bands acts as a resistance for downtrend movements and a support level for uptrend movements.
Traders look for two crucial patterns within Bollinger bands, including double top (‘M top’) and double bottom (‘w bottom’) patterns. There are multiple variations of these patterns.
M Tops: M top or double top patterns occur in an uptrend and are indicative of a bearish reversal. In this formation, the price hits a point high above the upper band, then retreats below the middle band. The band moves up again but stops short of the upper band. When the second surge fails to reach the upper band, it signals a weakening trend and likely reversal.
W Bottoms: The W bottom or double bottom formation is what happens when the M top formation gets flipped upside down. It signals a bullish reversal. It starts with the price plummeting below the lower band, then rallying past the middle band before dropping again. During the second drop, the price does not touch the lower band, then rallies past the earlier swing high to break out into a bullish reversal, ultimately forming a W.
On balance volume (OBV) is a volume-based oscillator and leading indicator. The signal quantifies volume, using cumulative trading volume to measure the strength of trends in upward or downward directions.
The idea behind on balance volume is that significant changes in volume often precede price movements, and that volume tends to be higher on days when the price moves in the direction of the prevailing trend. OBV adds volume during periods when the close is higher than the previous close, then subtracts volume during periods when the close is lower.
OBV technical analysis focuses less about the actual value of the volume. Instead, it looks at the rate of change or the rise and fall. This rise and fall, according to OBV theory, is what indicates the strength of buy and sell pressure. As OBV rises, it pushes buy pressure higher, leading to higher prices. When OBV is falling, it indicates a price decline is imminent.
Analysts use the OBV oscillator to identify support and resistance levels, then look for breakouts that precede price breakouts. They’ll look at OBV diverging from the prevailing trend, for example, which could indicate an upcoming bearish or bullish reversal.
We see this effect in action in the next graph. We see the price make a higher swing high while OBV makes a lower swing high, indicating a weakening uptrend. In a similar fashion, when the price hits a lower low and OBV makes a higher low, the downtrend is losing steam, and a bullish breakout could be upcoming.
This is where analyzing your other trading signals can come in handy. You might notice OBV diverging from the prevailing trend, for example, then use your other signals to better inform your next decision.
Stochastic oscillator is a leading oscillator that measures momentum, then uses that momentum to predict where markets will move next. The method was developed in the 1950s based on two key concepts:
Rule 1) Momentum always shifts before price
Rule 2) Variations in momentum can predict a change in market direction
With that in mind, stochastic oscillator analysis measures the relationship between closing prices over a given period as well as the trading range (high price and low price) of that period. Based on this relationship, the stochastic oscillator measures potential trend reversal, including overbought and oversold conditions.
The indicator oscillators between 0 and 100. These numbers indicate the bottom and top of the trading range over a specific time scale. That time scale is typically set to 14 periods.
The oscillator consists of two lines, including the slow oscillator (%K) and the fast oscillator (%D). Here’s how the formula breaks down:
Values higher than 80 indicate an overbought market, while values lower than 20 indicate an oversold market. However, these numbers do not always indicate a reversal. During strong trends, the price can hover at these extreme ends of the range for a lengthy period of time.
Stochastic oscillator analysis can, however, indicate a reversal or surge in momentum in certain instances. When crossovers and divergences occur over and under the signal line (%D), it indicates a reversal and surge in momentum.
Stochastic oscillator theory is also based on the idea that closing prices tend to hover in the upper half of the trading range during an uptrend while hovering near the lower half during a downtrend. Analysts will look for crossovers at the midpoint to indicate a shifting trend.
Bullish divergences occur when the price hits a lower low while the oscillator hits a higher low. Bearish divergences, meanwhile, occur when the price hits a higher high while the oscillator swings to a lower high. These reversals can also be confirmed when the price breaks past the most recent swing high (in a bullish divergence) or the most recent swing low (in a bearish divergence). Both of these things can confirm the reversal.
When the inverse of these bullish and bearish divergences occurs, it creates what’s called a bull or bear set-up.
During a bull setup, the oscillator hits a higher high as the price hits a lower high. When the price swings to a lower high, market momentum continues to surge, and the price will likely rise even further.
During a bear setup, the oscillator hits a lower low as the price hits a higher low. In this situation, progressive downward momentum indicates that a continued upward surge is unlikely even though the price is diverging upwards.