Btc

Forecasting levels is easier. Forecasting extremes is almost always harder. Highs and lows are properties of the path, not just the close. Price must actually reach the level, not merely close beyond it. Most models break on that distinction. 1) The data behave like noise Bitcoin is non‑stationary. Volatility shifts. Tails are fat. Jumps are normal. Terminal models compress everything to one number. Extremes require reasoning about the entire path. ...

My first forecast was simple: BTC would not drop below $90,000 in November. The bet looked reasonable from the data. But it lost. Here’s why. 1) I overestimated regime stability The month’s range looked stable: ~95–110k. Std was low; swings looked “orderly.” Mistake: I treated a local structure as durable. Regimes can switch faster than the data reveals. 2) I underestimated out‑of‑range probability The drop happened without a single clear trigger. That’s normal: price can break the distribution on order‑flow or liquidity alone. ...