First Crack At Releasing A Tesla Financial Model On Git

Based on the analysis I did of ARK Invest’s Tesla bull and bear cases, here and here, I decided to create my own financial model for Tesla growth. Tesla has a lot of moving parts, and Elon has famously said Tesla is made up of more than a dozen startups.

In true agile fashion, I thought it would be better to seek feedback on what I have created so far, rather than wait a long time and release a more complicated model without feedback. I’m following ARK’s footsteps and releasing my model on Github. I hope to incorporate some of the feedback and release a new model every 2 weeks. My goal for the model is two-fold: make it simple to create, and make it as accurate as that simplicity allows.

This first crack at a Tesla/EV financial model is missing many elements:

• No autonomous revenue.
• Missing many EV producers in China and Europe, such as Volkswagen, BYD, Li Auto, Xpeng, Renault, etc.
• Inability to save any simulation data.
• Inability to specify number of simulations to run.
• Not taking into account a variety of models and vehicle types that will be needed to achieve 10 million vehicles sales a year.
• Vehicles sold are only gathered annually, rather than quarterly.
• No factory start, completion, and maximum production.

It does include some things I am proud of adding:

• Specifies minimum and maximum ranges for a variety of variables.
• A rather clever way to figure Wright’s Law’s impact on revenue. This is based on the cumulative growth and dividing by multiples of 2 to see when cumulative production has doubled.
• Including energy generation and storage growth, a big miss in Ark’s model.
• Modeling the ratio of free cash flow (FCF) to revenue, and excluding all the messy stuff. This allows FCF-to-revenue to dip into negative numbers.
• Modeling the impact of interest rates on net present value for the next 10 years, and assuming constant cash flow after 10 years, and discounting that back to the present.
• Independent random variables for EV growth, energy generation and storage growth, Wright’s Law, interest rates, and FCF-to-revenue. In any year, these variables can show negative growth.
• The ability to include Tesla alone, Nio alone, or both together. There are more companies to add, as I said above.

Preliminary indications show the value of Tesla in 10 years is highly dependent on interest rates, FCF-to-revenue, and the speed of Wright’s Law in enabling cost declines. The maximum I saw energy generation and storage grow was close to 50% of total revenue. The model can show Tesla has a negative valuation after 10 years, which is possible if FCF dips into the negative and stays there. The range of value I have seen for Tesla alone is -$200 billion to +$1800 billion, which seems reasonable. Once I have the ability to save simulation data, I will analyze what the model says and fit a statistical distribution to match the data. At the end of every quarter, we’ll see how well the model did vs. reality, adjust the model minimum and maximum ranges, and release it again.

Feel free to branch off my Git branch and make your own changes, or download it and play around. Nothing is locked. You can find my Tesla model on Git here.

Any feedback is welcome — from “this model sucks and is a waste of time” to “this model is great, and thanks for making it!” Please add your comments below and I’ll respond when I can.

Warmest regards,
Vijay

Note: I own 3 shares of Tesla and Nio and am looking to add more Tesla in the coming week. Everything written here regarding the model should be looked at as entertainment and not financial advice. Please do your own due diligence before investing. We do not offer financial or investment advice of any sort on CleanTechnica.