The Klinger oscillator is a financial tool that was designed by Stephen Klinger in 1977 to predict long-term trends in money flow while also detecting short-term fluctuations. In addition, it predicts price reversals in a financial market by extensively comparing volume to price. Volume refers to how many units of a security are trading per unit of time.
The Klinger oscillator is based on the concept of force volume, which consists of volume itself, price trends, and temp (a number of if/then statements comprising volume/price).
The Klinger oscillator can be combined with other popular indicators, such as the Stochastic oscillator, in order to increase overall relevance, accuracy, and dependability.
Investors may also use the Klinger oscillator in conjunction with trendlines, price channels, or triangles to confirm price breakouts or breakdowns.
How It Works
In order to simplify such a technical topic, it is beneficial to illustrate the steps that are taken during the Klinger oscillator operation process.
Similar to most oscillators, the Klinger oscillator depends on differences between two specific exponential moving averages (EMA). An exponential moving average (EMA) is a statistical calculation used to analyze recent data points through the creation of averages within the series of data.
The Klinger oscillator measures the EMA of both price and volume. When a shorter EMA (shorter time periods) assumes a greater value than a longer EMA (longer time periods), it means that the price of a certain security is on an uptrend.
Conversely, when a higher EMA takes on a greater value than a shorter EMA, it suggests that the price of a specific security is experiencing a downtrend.
The default settings of the Klinger oscillator measure a 34-period EMA (a shorter EMA) and a 55-period EMA (a longer EMA).
In addition to EMAs, the Klinger oscillator uses volume force to measure the number of units of a security, open/closing prices, and if/then statements.
To generalize simply, the Klinger oscillator compares the EMAs of price and volume of a specific security in order to determine long-term trends in money flow.
Although it is hard to understand, the Klinger oscillator is an exceptional tool that is used extensively in the technical analysis community due to its predictive value.
Trading with the Klinger Oscillator
Regarding technical analysis and financial modeling, the Klinger oscillator consists of a centerline and two-colored lines being a blue line and a red line.
The red line is called the “Klinger,” while the blue line is referred to as the “signal.” The colored lines, specifically when they cross over one another or the centerline, are critical points to be aware of when conducting technical analysis. They are considered critical points because they determine the buy and sell signals.
A buy signal is formed when there is a crossover between the red and blue lines that occurs under the centerline. Once a buy signal is evident, it is likely that an investor will be a purchaser because they expect the price of a specific security to experience an uptrend.
A sell signal is formed when there is a crossover between the red and blue lines that occurs above the centerline. Once a sell signal is evident, it is likely that an investor will become a seller because they expect the price trend of the security to decline.
Limitations of the Klinger Oscillator
To some, it may seem that the use of the Klinger oscillator is a no-brainer due to its measurement and prediction of short and long-term price trends. However, it experiences some limitations that reduce the overall accuracy of the tool, resulting in a plethora of false signals.
Signal line crossovers occur very frequently. The regular occurrence makes it hard for the Klinger oscillator to filter out the worthwhile crossovers.
In addition to frequency, zero-line crossovers may cause issues relating to sustained price direction, making the indicator fail to predict trading opportunities.
As for divergence, the limitation of the Klinger oscillator is that divergence may occur too early, resulting in large missing segments of a trend. Sometimes, the oscillator’s divergence fails to predict the price reversal at all. However, it is expected as divergence is known for not being a reliable tool for predicting potential price reversals.