Financials Demystified: Long Term Liabilities Explained
The Investing for Beginners Podcast - Your Path to Financial Freedom
Deferred Taxes vs Long-Term Tax Liabilities
Dave explains deferred taxes, long-term tax obligations, and examples from Microsoft.
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This episode continues the Financials Demystified series with a practical, beginner-friendly breakdown of long-term liabilities on the balance sheet. Dave and Andrew focus on what these line items actually mean, why they matter, and how to use them to understand a company’s real financial risk.
They start with operating lease liabilities, what leases represent, why context matters, and how investors can compare lease obligations to profits, revenue, and even per-store economics. Then they move into tax liabilities, explaining the difference between deferred taxes and longer-term tax obligations (often tied to uncertain tax positions).
Key Topics Covered
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Long-term liabilities basics and how they show up on the balance sheet
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Operating lease liabilities and how to think about them
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Deferred taxes vs long-term tax obligations
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Long-term debt and why “laddering” maturities matters
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Practical metrics to evaluate liabilities and debt risk
Timestamps
01:44 – Operating lease liabilities explained
04:00 – Putting lease liabilities in context with profits
10:26 – Restaurant metrics: revenue, labor costs, and food costs
13:09 – Deferred taxes and long-term tax liabilities (Microsoft example)
18:42 – Long-term debt “peel the onion” (Danaher example)
20:10 – Debt maturity schedules and why staggered maturities reduce risk
24:49 – What debt details reveal about management and capital allocation
27:33 – ROIC vs cost of capital and why the spread matters
32:49 – Key metrics: debt-to-equity and net debt to EBITDA
35:21 – Quick checks: cash vs total debt and interest coverage ratio
Resources Mentioned
The Value Spotlight Newsletter: https://einvestingforbeginners.com/value-spotlight-newsletter/
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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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