brainfry turns live market data into probability cones and realized volatility statistics across the crypto universe. Every output is a statistical distribution under stated assumptions — never a signal, forecast, or recommendation.
Try a name (e.g. solana), a symbol (LINK), or paste a contract address.
Search any asset, fan its probability cone, and stress the assumptions. Everything is a statistical distribution — never a signal.
Find a token by name, symbol, or on-chain contract address. Paste a CA and the distribution is built on the spot — not just the majors.
Lognormal quantiles at the 5/25/50/75/95 percentiles, fanned across your horizon, with a hover readout of every percentile price at any date.
Annualized volatility over trailing 30/90/365-day windows, straight from daily log returns. Measured, not implied — no guesswork.
P(price ≥ target by horizon) under your assumptions, with the implied multiple on spot and the complementary probability.
Drive σ (volatility), μ (drift), and horizon yourself, on a log or linear scale. The cone re-fans live as you move the inputs.
Spot, rank, all-time high and its date, distance from ATH, and the worst peak-to-trough drawdown over the last year — at a glance.
At zero drift the median sits below spot by −σ²/2. We surface that lognormal property instead of hiding it, so you read the cone honestly.
A cross-asset correlation matrix and beta to bitcoin, computed from the same return series that drives the cones.
Pin the tokens you track and save cone setups — your σ, drift, and horizon — to return to with one click.
Add dated events — token unlocks, listings, anything — drawn directly onto the cone, so you can see what lands inside the distribution.
Pick a token, fan the cone, stress the assumptions.