Stochastics is a momentum indicator that shows where the most recent closing price fits in relation to the price range over a predetermined number of days, usually 14.
The indicator is based on the premise that prices have a tendency to close at or near highs when a security is in an upward trend, and at or near lows when prices are trending lower.
A reversal signal is given on divergence.
For example, if the market continues to make new highs but prices are tending to settle at the lows of the day, it can foreshadow a reversal in the uptrend. From a logical viewpoint, this makes sense. If prices are not able to settle at the highs of the day it suggests buyers are losing interest and taking profits sooner.
Whilst you do not need to know the formulae used to work out the indicator, it is useful to know the basis of its construction so you can apply it to your trading.
The indicator usually incorporates two lines, the %K and %D lines which oscillate between 0 and 100. The %K shows the latest close in relation to the average range of the last 14 days. The %D line takes a 3-day moving average of that line.
For ‘slow stochastics’, which is more commonly used, the data is further smoothed by taking a moving average (usually 3 or 5 days) of the moving average. In this situation, the %K line is the 3-day moving average of the simple 14-day stochastics (the original %D line), and the %D line is a 3 or 5-day moving average of the new, ‘slow’ %K line.
Stochastics is useful in determining whether a market is overextended. Usually, we would say that the security is overbought when the %K moves above 80 and oversold when it falls below 20. As with any indicator of this sort, a security can continue to rise despite being overbought and continue to fall when it is already oversold.
Here’s an example of stochastics ranging between overbought + oversold conditions. %K is shown in grey and %D is shown in red.
Source: ETX Capital
Buy and sell signals are given on crossovers – when the %K line moves above or below the %D line.
When the %K line (which is faster moving and more responsive to short-term movements in price) moves below the %D line, it is considered a bearish crossover. A bullish crossover occurs when the %K line moves above the %D line. This agrees with the premise of using multiple moving averages.
These signals are quite frequent and must be treated with caution – usually, traders look for other conditions to be met before a simple crossover is seen as a strong signal. If a crossover occurs whilst the market is considered overbought or oversold, it can have greater validity. As an example, if a bearish crossover occurs while the stochastics show overbought conditions (i.e. above 80), the trader would then look for a move back below 80 for confirmation.
Here’s an example of a bullish crossover, as %K line moves above %D line and out of the oversold territory.
Source: ETX Capital
Using the same chart pattern but applying the stochastics indicator in addition to the MACD reveals how the stochastics crossover provides an earlier signal of a trend reversal. This agrees with the principle that momentum leads price action while moving averages are lagging indicators that follow prices. The delay in the MACD signal is noticeable versus that provided by the stochastics. This is a good example of how it is useful to use more than one indicator, with a particular emphasis on using indicators that are based on different data inputs to derive their signals.
Stochastics can give earlier signals than MACD. Take a look at this example.
Source: ETX Capital
As with other momentum indicators, the divergence between the stochastics and the security’s price action can signal a reversal. Most often these may be used to confirm a crossover’s validity. For example, a bullish crossover accompanied by bullish or positive divergence would be a stronger signal. If the market is already in oversold territory and moves above 20, at the same time as a bullish crossover and positive/bullish divergence, it would be a very strong signal.
Our thanks to ETX Capital for supplying this introduction to stochastics.