Estimated reading time: 5 minutes
The stochastic oscillator is a major component of every proper options trading system out there. I personally employ the stochastic oscillator in a number of different systems that I have developed for binary options, mostly as a way to confirm a trading signal which I attain off a different indicator. In this respect, the stochastic oscillator is always a bit like the cavalry riding to the rescue: as one embroils himself in a number of often dubious-looking indicators and trading signals, it always comes to confirm or to deny one’s findings, making it clear whether one is right or wrong. As such, the stochastic oscillator can in fact be used by traders who have no particular understanding of how it’s defined or how it works from a technical angle. As long as they know what it points to and how it relates to other indicators, its conclusions can be put to use I suppose, but by understanding what it really is, and how it accomplishes what it does, traders will be able to gain a better feel for any given market-condition, and they will in fact be able to get a lot more out of the stochastic oscillator than otherwise.
The stochastic oscillator is an indicator which compares the current price of an asset to the range that its price has covered over a defined period of time in the past. With that in mind, it’s easy to see how the stochastic oscillator is in fact a tool based on the momentum of the asset-price, using it to predict potential upcoming retracements. The trader can then use those retracements to place his/her trades in a manner that will hopefully be profitable.
The nature of the stochastic oscillator is quite obvious in the mathematical formula which defines it too: %K (which is the stochastic oscillator) = 100*[(Current Price-L14)/(H14-L14)] where H14 is the 14-day high of the asset price-action and L14 is the 14-day low. In the formula above, it is obvious that we’re comparing the current price with the full spectrum of the price-movement over the past 14 days. 14 days is a sort of a default period for the stochastic oscillator, but obviously, this part of the setup can be altered and fine-tuned in order to change the sensitivity of the oscillator in certain cases, as it may often turn out to be too sensitive indeed. A much-too-sensitive stochastic oscillator will give out many false signals thusly reducing its efficiency.
How exactly do we use the stochastic oscillator though? In order to be able to use it in a graphical manner which will allow us to draw conclusions off a chart, we’ll need to use another component for it: the 3-day (period) moving average of %K, which is designated %D and which will be the second line of the oscillator under out chart. Why do we need %D? Here’s the story:
%K will point at overbought and oversold situations in an asset-price quite accurately, which – logically – should be enough to provide enough of a clue towards a trend-reversal. %K is a range-bound quantity (always between 0 and 100) – which is why it is called an “oscillator” to begin with. When it’s above 80 (or in some cases even 70) it points at an overbought asset-condition, in which case, a downward retracement is in the books. Similarly, if %K is below 20 (or in some cases 30), we have an oversold situation, with an upward reversal in the books. Why do these seemingly “magical” numbers indicate oversold/overbought situations though? Simple: if the stochastic oscillator hits a value of 80, that means that the current closing price is above 80% of the closing prices registered during the period for which we had the oscillator applied. Similarly, if the stochastic oscillator produces a value under 20, that means that the closing price of the asset is essentially below 80% of the closing prices of the last 14 or so days.
While all this is indeed as straightforward as possible, unfortunately, it does not quite work that way. Some asset prices can maintain overbought and oversold situation for a long time without a retracement, so the stochastic oscillator fails to properly predict trend-reversal based solely on %K. This is where %D comes into the picture. Because the stochastic oscillator essentially identifies shifts in the momentum of the price-action, and because price in general follows momentum, when the two lines of the oscillator (%K and %D) cross in an oversold or overbought situation, that’s when a large momentum shift is in the works and obviously, that’s when trend reversals will occur.
Another way to use the stochastic oscillator for predicting trend-reversals is to watch for divergence between the price-trend and the oscillator itself. For instance, if we have a bearish trend going lower while the stochastic oscillator reaches a higher low, the bearish momentum may indeed have reached its end.
As said above, the sensitivity of the stochastic oscillator can be adjusted according to one’s needs. Thusly, slow stochastics and fast stochastics will result, with the fast stochastics representing the more sensitive side of the spectrum. To get slow stochastics from the fast ones, traders will apply a 3-day moving average to %K, a proven way to improve the quality of the signal: this way, the number of false crossovers will be reduced and traders will find it much easier to make heads and tails of the stochs signals. An additional 3-period average can also be applied, which will result in the slow stochasictics’ %D. Obviously, with the above said in mind, it’s clear to see that the %K of the slow stochastics is the same as the %D of the fast stochs. Someone quite accurately said that the difference between slow and fast stochastics is the same as the difference between a fast, agile sports-car which picks up and reacts to changes in direction quite instantly, and a limousine, which is slow to react, but carries much more weight.
Now that you hopefully know all there is to know about the stochastic oscillator, you won’t just be able to understand technical analysis articles better, you will also be able to put this potent weapon to use in a much more efficient manner.
Philip Thalberg has been trading options for 7 years now. Based in Toronto, he’s developed/adapted quite a few trading systems/strategies to hit profit-territory, an undertaking at which he has thus far been quite successful. He has “built” his own options trading robot which he uses to help other traders too.