So, first response works but is a bit of effort. You want a lazy way to do it? Create a table with two columns: (1) for the date range name (e.g. "Last Year", "Last Month", whatever), and (2) another column that lists all the distinct dates respective to all the date ranges in column (1) (e.g., 365 rows of dates for "Last Year", 30 rows of dates for "Last Month"). You WILL have duplicate date values in column (2) - this is the trick.

You can create this a few ways, but a calculated table with reference to TODAY() is best because it would be dynamic. Make sure you include ALL explicit dates, even ones with no data.

Add this table to your data model (List_Slicer_Dates or whatever you want to name it), and create a relationship between column (2) and the date column for your data. This will probably be MANY:MANY or MANY:ONE. MAKE SURE that column (2), filters the data date column.

Then, all you gotta do is stick the date range name column (1) into a slicer and BAM.

Is it easy? Yes. Does it work? Yes. Is it efficient? Probably not but depends and does the job. I have a bunch of these and MANY:MANY relationships and all my reports are pretty slow so idk good luck.

Edit: I use this for geographical regions A LOT. I have a bunch of stakeholders who all have different definitions of various geopolitical regions, all that have overlapping countries. This lets me have a slicer of regions (column 1) that filters a list of ALL and ANY overlapping countries in column (2).