Sixteen years, four brutal crashes, one direction.
Bitcoin went from a fraction of a cent to over $120,000, a factor of more than 200 million. Every chart here uses a log scale. It's the only honest way to show percentage moves evenly across that range.
The crashes are savage and regular — −93% (2011), −85% (2015), −84% (2018), −77% (2022) — yet the long-run direction is unmistakably up.
overview
Where the long run points.
Bitcoin's 16-year path follows a power law — a straight line on a log-log chart. Four independent methods agree on roughly where that trend lands by 2034.
When methods this different land within ~15% of each other, it's a real signal about the central tendency, not a price target. The realistic spread around it is enormous.
compare_all
rainbow
You can't time the price.
We backtested every forecasting model the honest way: train on the past, predict the future it hadn't seen, roll forward, repeat 180 times. The benchmark to beat is the dumbest possible forecast, “tomorrow's price = today's price.”
Almost nothing beats it.
backtest_skill_heatmap
hurst
foundation_ensemble
The cycle is real — and quietly fading.
Price level is unforecastable. Cycle structure is not. A wavelet analysis, which finds repeating rhythms, reveals a persistent multi-year cycle running across the whole history.
It's close to the famous “4-year halving cycle,” but slightly shorter (~3.5 years) and weakening as the market matures. Betting on a clean 4-year repeat means trading a signal that's going quiet.
wavelet_scalogram
seasonality
valuation_overlays
lppls
Go deeper on the cycle.
Companion report — we extended this cycle 10 years out & stress-tested it →Did the models call the cycles?
The cycle is real. The fair question is whether our models actually caught it. So we graded them the honest way. For each four-year-cycle turn, and using only the data available at the time, did each model call the turn in advance, lag it, or miss it?
The turns are the well-known ones: peaks in late 2013, 2017 and 2021, bottoms in early 2015, late 2018 and late 2022.
btc_cycle_scorecard
forecast_baselines_expanded
Risk is the one thing you can model.
The good news the backtest surfaced: volatility is forecastable even when price is not. A simple volatility model beats the naïve baseline by ~6.5%. Modest, but real and repeatable, unlike anything in price prediction.
And the risk that matters most — crash risk — is far worse than “normal” math implies.
garch
regime_hmm
evt
sim_jump_diffusion
The honest synthesis.
This is not advice to buy or sell. It's a map of what the data supports and — just as important — what it doesn't.
Trend points to mid-six-figures by the early 2030s if history holds. But the uncertainty is enormous and the timing is unknowable.
Unpredictable. Today's price is the best forecast of tomorrow's. Ignore confident price targets.
Below trend, in the cheaper accumulation part of the cycle, no bubble — by every classic gauge.
Elevated and fat-tailed. Plan for a −30% day in any year and a −70%+ day in any decade.
- —One price series. No on-chain, derivatives, or order-book data.
- —The long-horizon forecasts can't be validated; with 16 years you can't backtest an 8-year prediction. Those cones are scenarios, not validated forecasts.
- —The trend assumes the past pattern continues. Power laws break; past growth doesn't guarantee future growth.
- —Forecast bands are imperfectly calibrated — too wide at short horizons, over-confident at long ones.
- —Descriptive ≠ predictive. These models describe what happened; they don't predict what's next.
Descriptive research, not financial advice. Bitcoin is volatile and can lose most of its value in a year — as it has four times in this dataset.
Appendix — all 14 charts & model inventory →