How the classic cycle indicators work, and what they actually tell a long-term holder.
Eleven years of daily Wikipedia readership tested against bitcoin's price at every lag from −60 to +60 days. Attention peaks one day after the move, not before — and today's reading is the lowest of the whole record, inside a quiet spell that has run 452 days and has not ended.
Our own statistical model was replayed over thirteen months and marked against what bitcoin actually did — 766 forecasts, one by one. It lost to the laziest benchmark there is: assuming next month's price is today's.
Uptober, the September effect and sell in May, checked against our own 178 monthly bitcoin returns. The pattern is in the data — and 15 observations a month cannot tell it apart from luck.
Bitcoin’s 90-day realized volatility reads 34.6% a year against a 62.1% median since 2011. Fifteen years of the trend: where the fall stalled, why dropping the first three years halves it, and why a calmer average is not a safer asset.
What Deribit's DVOL index measures, how a year of implied volatility compared with what bitcoin then did, and why ether's reading never came down to bitcoin's.
Two halvings, 1,440 days apart, normalised to their own dates: where the 2020 and 2024 cycles agree, and where they differ by a factor of four.
What perpetual funding is, what 0.01% per eight hours costs over a year, and what seven years of our own data say about the extremes.
What the alternative.me index is actually built from, why it covers bitcoin only, and how often extreme fear and extreme greed have really occurred.
Price divided by its 200-day average. What eight years of data say about the distribution, the 2.4 threshold, and why we rank it as a percentile.
The average weekly close over four years. How often price falls below it, why Bitcoin's baseline behaves differently from Ethereum's, and today's reading.
