A Beginner's Guide to Stochastics

The term "stochastic" first evolved in mathematical probability theory. While many activities and events are predictable based on probability, there are some events that appear to be random or unpredictable. These events are often called outliers. The field of stochastics can be applied to science, language, art and even music. It is a study of the fact that the same input can generate multiple different outputs. In finance, stochastics has a very specific application: the stochastic oscillator.

History of Stochastic Oscillator

In the 1950s, Dr. George Lane began using mathematical stochastic theory to predict stock behaviors and pricing. Essentially, Lane theorized the future price of a security could be estimated by looking at its current price compared to a recent price range. Using this model, Lane thought he could predict turning points in price. Financial modeling was not as popular in the early days of the securities market. Today, computers have revolutionized trading. Complex stochastic models can be input into a computer with access to trading, and the model can then be applied to thousands of trades over the course of a single day. The practice has come a long way since its original roots.

Application of Stochastic Oscillator

The oscillator, whether it is being used in a simple hand calculation or a complex computer model, is essentially the same. The basic principle is this: a security's price has a range from 0 to 100 percent during a given period. The price of the security will approach one of the extremes immediately prior to making a drastic shift. So, in a simple model, imagine a widget that trades between $5 and $20 in a 2-year period. For the past six months, the widget has been trading at an average of $12. Now, in the past month, the widget has been trading at $7, which is fairly close to its 0 percent number of $5. According to stochastic theory, this indicates the price of the widget will jump much higher in the immediate future.

Using Stochastics in Trading

Not all investors should rely on modeling when making trading decisions. In fact, stochastic models are notoriously used incorrectly by novice investors. Many markets present intangible factors that cannot be correctly considered when it comes to modeling. For example, outstanding liabilities, changes in ownership and other considerations cannot be made. There are some markets, though, where stochastic modeling works much better. Two examples include commodities trading and foreign exchange (forex) currency trading. 

Forex Trading and Stochastic Modeling

Forex trading is a popular arena for the application of stochastic models. Here, the two basic stochastic lines are used: percentage of K is a line indicating the main line price; percentage of D is the moving average of the percentage of K, or the range. Watching these two lines interact can tell you when to buy and sell. Generally, you should sell a currency when the percentage of K rises above the 80 percent mark and then falls back slightly, indicating it will take a price turn. On the contrary, you should buy when the percentage of K falls below the 20 percent line and then rises, indicating it will turn the opposite direction.

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