Two Independent Bitcoin Cycle Models Land Within 40 Days of Each Other
Someone on X recently published a cycle-timing model I hadn't seen before: bull phases run a fixed 1,064 days, bear phases run a fixed 364 days, and that pattern has repeated across three full cycles. Running it forward, they land the end of the current downtrend on October 9, 2026.
That's worth a second look, not because the model is airtight, but because of what it doesn't share with a framework I published a few days earlier.
Their framework
The logic is straightforward: bull and bear phases each have a fixed duration, and it holds across every cycle so far.
- 2015→2017 ran 1,064 days up, 2017→2018 ran 364 days down.
- 2018→2021 ran 1,064 days up, 2021→2022 ran 364 days down.
- 2022→2025 ran 1,064 days up, 2025→2026 ran 364 days down.
Extending the same duration forward puts the end of the current downtrend on October 9, 2026. Notably, this method never looks at the halving date at all — it's purely about whether phase lengths repeat.
My framework
The 500/500 rule anchors on the opposite variable — the halving itself, a fixed protocol-level calendar event:
- The 2015 bottom sat 511 days before the July 2016 halving.
- The late-2018 bottom sat 504 days before the May 2020 halving.
- The 2022 bottom sat 504 days before the April 2024 halving.
- Projecting the next halving to Q1 2028 and running the 504-511 day window backward lands the accumulation window on November 9-16, 2026.
This method never looks at how long bull or bear phases themselves last — only at distance to the halving.
Why the overlap matters
The two models share no inputs. One is about the self-similarity of bull/bear phase lengths; the other is about the fixed distance from bottom to halving. When two historically-derived, mutually independent methods land the same event — the next cycle's turning point — within 40 days of each other, that convergence — call it a cross-validation of the two models — is worth recording, even though either model on its own is just an extrapolation from three historical samples.
Worth flagging: I can't independently verify the follower count or track record behind the original post — I'm citing the published reasoning, not vouching for the source.
Where this breaks down
- Both frameworks are extrapolations from history, and three cycles isn't a statistically significant sample by any rigorous standard.
- "Turning point" and "accumulation window" aren't quite the same concept — one estimates where a downtrend ends, the other estimates where a buying window starts. They're related but not identical, so this cross-validation is about a rough time band, not a single precise event.
- The real confirmation still has to come from on-chain structure at the time. The calendar overlap tells you where to point your attention, not where to click buy.