Data Trends for Investment Professionals


Alternative data sheds light on Tesla’s mysterious delivery numbers

Tesla’s strong Q3 delivery numbers – more than doubling from the prior quarter – was good news for the company. But a new report on mysterious lots of Tesla vehicles appearing across America has fanned speculation that those numbers may not be what they seem. Quandl’s alternative data also indicates that there may be more than meets the eye.

UPDATE (October 26, 2018): The Wall Street Journal is reporting that the FBI has stepped up a criminal investigation of whether Tesla is misstating production figures.

On Tuesday, October 2, Tesla announced a doubling of deliveries in the third quarter to 83,500 vehicles, up from 40,740 in Q2, beating most estimates and signalling that the company may finally be resolving its perennial production problems. 

While a boost for Tesla, there remains a mystery about what the delivery numbers actually mean. The New York Times on Monday reported that large numbers of new vehicles are being found in multiple locations across the U.S., with online evidence raising questions about production, logistics, quality, and possibly demand.

The Times offers speculation about possible reasons for these mysterious lots of Teslas, and none of them are particularly positive for the company. The paper notes that there may simply be an ongoing problem with getting cars into the hands of customers, something admitted by the company with Musk’s September description of Tesla experiencing “logistics hell”.

Another possibility is that Tesla may have built more rear-wheel-drive Model 3s than it could sell. The delivery period for rear-wheel models is four weeks while it’s four to twelve months for the pricier all-wheel-drive models, Barclays Capital analyst Bryan Johnson said.

The most ominous suggestion for Tesla and its investors is that demand for the company’s mass-market Model 3 is slipping as a promised price drop hasn’t materialized. While the company early this year said it had more than 450,000 global reservations for the sedan, it’s possible that many of these pre-booked customers are now balking at a US$50k-$60k price tag after being pre-sold on a US$35k one.

Tesla delivery numbers and the case for skepticism


Alternative Data vs Tesla Reported Deliveries

Auto sales data from Quandl paints an accurate picture of “cars-in-hand” for Tesla vehicles.
To learn more about our alternative data, please contact us.

Quandl clients have been able to generate highly accurate projections of Tesla’s “cars-in-hand” through the use of alternative data comprising U.S. auto insurance registrations. As insurance is mandatory for U.S. drivers, new car deliveries almost perfectly correlate with the sales of new auto insurance policies.

“As Quandl data tracks action by owners of new Tesla models, we can very safely assume that it indicates a successful delivery to the end customer,” says our Chief Data Officer Abraham Thomas. “Because there is a wait list for cars, it has been assumed that Tesla’s reported delivery numbers track very closely to sales. But the widening gap between our insurance data and Tesla’s delivery numbers suggests that the company’s definition of ‘delivery’ may not necessarily reflect a customer taking ownership of a vehicle.”

“This could support the ideas posited by the NYT article, although not necessarily the worst-case scenario of sliding demand,” says Thomas.

With Quandl data available at a weekly level for the Tesla Model 3 and at an aggregate level for all Tesla models, we’ve found that this tracks actual Tesla deliveries with high accuracy. However, you’ll notice a widening gap between reported production numbers, Tesla delivery numbers, and Quandl’s derived numbers. The free VIN tracker from Bloomberg tracks unusually closely to Tesla’s reports, causing further speculation. “It’s hard not to look at that and wonder whether somewhere, somehow, the VINs are being gamed,” says Thomas.

Improve your foresight with alternative auto data

At Quandl we take data that you’ll never see in a market feed and put it into your hands. Our data science team uses our proprietary technology and their expertise in financial engineering to find new datasets and assess them for predictive power, reliability, and compliance. Then, we take those datasets and put them into a form that professional investors can use to improve their trading decisions.

In the case of production numbers for Tesla and other carmakers, our auto insurance data has provided very solid clues about automaker performance. Investors can use our auto insurance data to get a daily count of new car policies, conveniently divided by manufacturer, to gain an insight into the number of vehicles that were built and delivered during a quarter — all well before shipments or earnings are typically announced.

Before the numbers are tallied and announced for Q4, will you be guessing if Tesla will be hitting their production goals? Or, will you know?

If you are an institutional investor interested in insurance data, or other valuable alternative datasets, please contact us.

Quandl has compiled this material from sources believed to be reliable, but no representation or warranty, express or implied, is made to its accuracy, completeness or correctness. Nothing in this material constitutes legal, accounting, tax or investment advice. Neither the information provided nor any opinion expressed constitute an offer to sell or a solicitation of an offer to buy any securities or to take any deposits or provide any financing. Past performance does not guarantee future returns and a loss of original capital may occur.

To the full extent permitted by law neither Quandl nor any of its partners, nor other individuals including employees, accept any liability for any direct or consequential loss resulting from any use of this material or the information contained herein. This report is for informational purposes only and is not intended to provide specific financial, investment, tax, legal or accounting advice, and should not be relied upon for those purposes. You should not act or rely on the information herein without seeking the advice of a professional.

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