Navigated to The 4-Year Cycle Is Wrong (Math Proves Bitcoin's Real Pattern) | Stephen Perrenod | BFM218

The 4-Year Cycle Is Wrong (Math Proves Bitcoin's Real Pattern) | Stephen Perrenod | BFM218

Dec 29, 2025
1h 20m

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Episode Description

Stephen Perrenod is an astrophysicist and technology consultant with over 30 years of experience in high performance computing. He’s the author of two books on cosmology and has been writing and speaking about Bitcoin for a decade.

https://x.com/moneyordebt


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🕑 TIMESTAMPS

00:00 - Introduction and Context of Bitcoin Bubbles

02:26 - Alchemy, Energy, and Bitcoin's Value

04:55 - Power Laws vs. Exponential Growth in Bitcoin

07:59 - Bitcoin vs. Gold: A Comparative Analysis

09:59 - Market Dynamics: Bitcoin's Correlation with Gold

12:33 - Understanding Bitcoin's Value Proposition

15:12 - Volatility and Long-Term Perspectives on Bitcoin

27:41 - Understanding Bitcoin's Value and Persistence

30:08 - The Kelly Criterion and Optimal Portfolio Allocation

35:05 - Risk Assessment and Cash Allocation in Investments

39:06 - Evaluating Historical Performance and Future Projections

44:31 - The Power of HODLing and Investment Strategies

48:27 - Mathematical Models and Future Price Predictions

55:37 - Understanding Volatility and Market Behavior

58:07 - Analyzing Bubbles and Market Cycles

01:02:42 - The Evolution of Bitcoin's Market Dynamics

01:10:39 - Predictability in Bitcoin's Price Movements

01:16:30 - The Future of Bitcoin and Market Predictions


ℹ️ EPISODE SUMMARY

Bram Kanstein and Astrophysicist Stephen Perrenod discuss Stephen’s latest findings from the Scientific Bitcoin Institute. Is the Bitcoin four-year cycle a myth? Stephen breaks down the Power Law math that dismisses traditional cycles and predicts a new timeline for future bubbles. We explore why Bitcoin grows 100,000x faster than gold, the "alchemy" of the Nakamoto consensus, and why the network effect makes Bitcoin a meta-network unlike any other asset. Stop looking at linear charts; the real signal is in the log-log.

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