Introduction
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This is Ken Leoni Vice President of Marketing here at Stock Rover. In this video, I will explain what custom metrics are and their benefits. And then I will show you how custom metrics can be viewed in the Table as columns or used in filtering expressions in screeners to do more advanced screening. Lastly, I’ll show how to create a custom metric from scratch.
Before jumping in, a quick word about Stock Rover’s out-of-the-box metrics.
Stock Rover comes with some 700+ metrics that encompass a broad set of categories. Also included are advanced metrics such as the Piotroski F-Score, Price to Graham Number, Shiller P/E, Margin of Safety, Beneish M-Score, and the Altman-Z score.
What are Custom Metrics?
- As the name implies “Custom” Metrics are custom or new metrics that you create using equations.
- Equations allow you to create your own custom calculation format based on existing Stock Rover metrics.
- Custom Metrics can use both current and historical values in their equations
- Metric values can be returned as decimal, dollar, or percentage
When do you use Custom Metrics?
Although Stock Rover comes with some 700+ metrics, Stock Rover may not have the exact metric you are looking for.
Custom Metrics also allow you to reference both current and historical values when computing a new metric, whereas the Stock Rover out-of-the-box metrics only reference current values.
Once you create a custom metric, it is included in the Metric Browser as if it was built into the product. The Stock Rover Metric Brower provides details on all Stock Rover metrics available to you, including all the out-of-the-box metrics, as well as any custom metrics you create.
Once you create custom metrics, the Metric Browser will display a folder called Custom Metrics. The folder contains a list of all the custom metrics. We see 2 custom metrics have already been created.
You use custom metrics to calculate something new using existing metrics.
For example, we’ll select a custom metric that was previously created, called Return vs Drawdown. This custom metric provides a sense of the risk/reward characteristics of a given ticker. The custom metric calculates something new using an equation that takes the trailing twelve months of return for a ticker and divides it by the absolute value of the maximum 5-year drawdown and then multiplies by 100. The higher the equation result the better.
To reference historical values
A common use case for custom metrics is to perform a calculation using historical values.
We’ll select a metric called “ROIC” otherwise known as return on invested capital verse 3 Year Average. This custom metric consists of an equation that is referencing historical values to compute the 3-year average trailing twelve-month ROIC value. The 3-year average ROIC is then subtracted from the most recent trailing twelve-month ROIC value. The ROIC vs. 3-Year Average custom metric shows how the current ROIC is faring relative to the last 3 years, where the higher the value, the better.
Where do you use Custom Metrics?
Display in the Table
You can display Custom Metrics in the Table where you can then compare the metric’s value across tickers.
For example, let’s load the table with the passing tickers a growth at a reasonable price screener, and let’s select the Profitability View in the Table. Here we see that that the custom metric ROIC vs. 3-Year Average has been added as a column to the Profitability View. We can now see the ROIC vs 3 Year Average custom metric value for each ticker that has passed the growth at a reasonable price screener’s filtering criteria.
Custom Metrics behave exactly like out-of-the-box metrics. For example, we can sort the Table based on the custom metric. we can also filter the metric
To remove the column from the View we’ll go to the column heading and select “Remove Column”.
I’d like to add the ROIC vs. 3 Year Average custom metric back into the Profitability View. I’ll start by selecting “Add Column”. I can either “search” for the custom metric by name or browse. Let’s browse, We’ll select the custom metrics folder and our custom metric.
Notice the custom metric appears immediately after the Company column. To reposition the column simply go to the column header – drag and drop. I’ll move it next to ROIC.
As we can see adding custom metrics to the Table is simple and quick.
Reference them in the filtering criteria of a Screener
Let’s go to the Screener Manager and select my demonstrate ROIC verse 3-year average screener. Just like out-of-the-box metrics, custom metrics can be referenced as filtering criteria in a screener. In our example, we are continuing with our demonstrate ROIC verse 3-year average screener custom metric and filtering on a threshold value greater than 25. We can 14 tickers have been returned.
We can easily edit our filtering criteria. Let’s change to thirty. Let’s save.
For clarity, our screener has a single filter, keep in mind your screener’s criteria can be based on any combination of out-of-the-box and custom metric filters.
When I select “Run In Table” Stock Rover this shows the passing tickers and the values of the custom metric that met our filtering criteria. When I switch to the Profitability View, I see the passing tickers and the custom metric along with out-of-the-box metrics displayed.”
Creating a Custom Metric
Custom metrics are always created from within the Table.
I’ve selected the “Growth” View and loaded it with results of the “Top Stocks” screener. Here we see the that EPS QoQ Change metric is the quarter-over-quarter change in earnings per share between this quarter and the same fiscal quarter one year ago.
I’d like to add a custom metric that also shows the earnings per share percentage change of the most recent quarter from 1 quarter ago.
We’ll go to “Actions” and “Create Custom Metric”. The first thing we’ll want to do is give the custom metric a name and let’s give it a description as well. The “Display Format” will be “Percentage”. Under “Includable Metrics” “Quick Add (Search)” we want to search for EPS. Notice EPS shows next to “Test” with a now suffix and also in the Equation Editor. The now suffix indicates that Stock Rover is maintaining history. Metrics that don’t have history maintained do not appear next to Test or have a suffix.
Let’s click on edit. We can see that Stock Rover is maintaining history for the trailing twelve months going back 10 years, for calendar years going back 10 years, and for quarters going back 9 quarters. We want to start with the most recent quarter. We want to subtract. And let’s select EPS again, we’ll click on edit because we want to subtract 1 quarter ago. Once you are familiar with the Stock Rover equation syntax, you can also type freeform into the Equation Editor. We’ll wrap in parenthesis and divide by EPS Q1. Let’s multiply the entire equation by one hundred.
We’ll click “Test” to verify the syntax and we can see that Stock Rover tested it against IBM at 118.9%. We’ll create., We now see our Custom Metric in the Table along with a description. We’ll just drag it and drop it over.
The workflow is that you create the custom metric from within the Table so the metric can be displayed as a column in the table for comparative analysis. Once you’ve created the custom metric it can be added to any View in the table. It can also be referenced as part of a screener’s filter criteria in the Screener Manager as we showed earlier.
Summary
In summary, Custom Metrics extend Stock Rover’s power.
- Custom Metrics allow you to calculate something new or different
- As well as reference historical data
- Custom Metrics can also be added to the Table for comparative analysis
- As well as referenced as filtering criteria in screeners
I hope you found the video useful. I encourage you to explore Stock Rover and see all that it has to offer, as well as check out our other educational videos on our website. Thank you for watching.
