TASC's June 2022 edition Traders' Tips includes an article by John Ehlers titled "Ehlers Loops. Part 1". This is the code implementing the price-volume Ehlers Loops he introduced in the publication.
John Ehlers developed Ehlers loops as a tool to visualize the performance of one data stream versus another, both filtered and scaled. In this article, the author applies his concept to exploit and/or dispel the dogmatic principles of reliable price-volume relationships.
The script offers two different ways to visualize Ehlers Loops:
Oscillators (default option)
In this implementation, filtered and scaled volume is plotted along with filtered and scaled price as zero-mean oscillators. Observation of the relative direction of volume and price oscillators can be discretionarily used to interpret and predict market conditions. For example, it is generally assumed that an increase in volume and an increase in price define a bullish condition. Similarly, decreasing volume and increasing price are generally considered bearish. A decrease in volume and a decrease in price is considered a bullish condition. The increase in volume and decrease in price is often thought to be bearish.
This Crocker-style visualization displays filtered and scaled price against filtered and scaled volume for the selected timespan. Fluctuations in volume are plotted along the x-axis, while price changes along the y-axis. This way of visualizing the Ehlers Loop allows you to analyze the curvature and directional path of the price in relation to volume, offering a different comparative perspective. The boundaries of the price and volume scale on the Ehlers Loop Crocker-chart are presented in standard deviations. Deviations can be used to predict possible future price or volume fluctuations. The expected probability of potential reversals is 68%, 95% and 99.7% at one, two and three standard deviations, respectively.
The following steps are used to build an Ehlers Loop:
• Both price and volume are filtered to be band-limited signals. This is done by applying the high-pass Butterworth filter in combination with the low-pass SuperSmooth filter.
The cutoff wavelengths of the high-pass and low-pass filters are defined by the input parameters HPPeriod and LPPeriod, respectively.
These values change the appearance of the Ehlers Loops and can be customized to your trading style.
• The filtered price and volume time series are then scaled in terms of standard deviation by dividing each by their root-mean-square values.
• The resultant price and volume data are plotted as zero-mean oscillators or as a scatterplot.
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