Thanks. I assume that US Bank does not make their RV data available…?
That’s correct as far as I know, and I’ve looked, extensively, over the course of half a dozen leases. The only way to get it (again, as far as I know) is to ask brokers or dealers who have access to expensive software. Problem with that is you’re only going to end up getting info one vehicle at a time.
Question about your sheet - I see you’ve listed all of the RV terms but did not list what the underlying mileage assumption is for all of them. Assume they’re all RVs for 12k miles? Might wanna just put that in the header or something for reference.
Actually it’s 15K:
The residuals in this guidebook are based on 15,000 miles per year (1,250 per
month)
The PDF on page 5 has information on what to add to the RVs for various other mileage.
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People have been mucking around with the spreadsheet (most of the data was missing?) so I reverted it and disabled edit access. If you want to sort the data, make a copy of the document.
@Rsantoro12 if you still want to work on it let me know your Google ID and I’ll give you access. Your changes are still there in the history; I can copy your sheets back in.
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Seems like this would be interesting to grab the csv, then use that to do some interesting leasehacking, no?
- Didn’t follow the pdf - how do you calculate the MF from this document?
- I also see the allydealer website, they list specific specials which override. Would be interesting to exhaustively crawl that to amend csv extract of the pdf.
- Lease arbitrage - calculate the effective residual market value from the csv and msrp, find 2 or 3 year old vehicles of the same make/model for sale on carvana (or similar sites), estimate terminal value from carvana prices to scrape out positive equity at the end of the lease instead of turning in.
You don’t. This is focused on extracting RV data, not MF.
I wouldn’t use this as any sort of metric to evaluate a lease. What has positive equity today could be thousands in the hole tomorrow, let alone 3 years out. I wouldn’t trust past numbers on a particular model to be gospel moving forward. Too many variables can affect future values