Odd deferred revenue disclosures (Netflix example)

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In this episode of Financials Demystified, Andrew and Dave continue working down the balance sheet by breaking down current liabilities—what they are, why they matter, and what they can reveal about how a business funds operations in the short term.

They also connect current liabilities to working capital management, showing how things like accounts payable and deferred revenue can impact cash flow and business quality. To make it practical, they use examples like Campbell’s, Adobe, GameStop, and Netflix—highlighting how the same “category” can look totally different depending on the business model.

Key Topics Covered:

What current liabilities are

Accounts payable and what it reveals about working capital and cash flow

Common current liability line items

Deferred revenue (why it’s a “liability” that can actually be a positive)

Days payable outstanding & the working capital cycle

Timestamps:

00:00:15 – Financials Demystified continues

00:00:48 – Definition: current liabilities

00:01:38 – What current liabilities can reveal 

00:04:39 – Example: Short-term borrowings, dividends payable, taxes payable

00:08:13 – Deferred revenue: what it is and why it’s not like “real” debt

00:11:28 – Netflix deferred revenue “weird tidbit” 

00:13:32 – Income taxes payable

00:17:20 – DPO formula

00:20:24 – Working capital cycle formula 

00:35:46 – Wrap-up

Resources Mentioned:

The Value Spotlight Newsletter: https://einvestingforbeginners.com/value-spotlight-newsletter/

Blog post: https://einvestingforbeginners.com/free-cash-flow-yield-daah/

Infographic: https://www.linkedin.com/feed/update/urn:li:activity:7406343606875140096?utm_source=share&utm_medium=member_desktop&rcm=ACoAAD4eKMMBf-41eiJkuqE7j8nT8vhR0cxiYKE

Have questions or want your story featured? Email the show at newsletter@einvestingforbeginners.com or comment below. Your feedback shapes the podcast!

Remember, invest with a margin of safety—emphasis on the safety. Have a great week, and we’ll talk to you next time.

Timestamps are generated by artificial intelligence, and are not 100% accurate depending on the platform used for listening.

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