Risk, valuation and cycles
Risk bands, logarithmic regression, dominance, drawdown, ROI by cycle and the technical set — across 14 assets, on daily close.
Every historical value on this site could have been computed on the day it happened. Expanding-window normalisation, daily close, and every definition versioned in public — including the studies that failed.
Risk tops when separation from the 365-day mean peaks — not when price peaks. The two are weeks or months apart.
A risk metric is normally scaled between its own minimum and maximum. Take those from the whole history and every point in 2015 is drawn using the range of 2021 — a number nobody could have computed at the time, on a chart that exists to tell you what to do today. It renders perfectly. It is still a lie about the past.
Ours expands: each day is scaled only against the days before it. Backtests come out worse and the chart is harder to sell. It is the only version that means anything.
Title, the date it was computed, the version of the metric that produced it, and one plain sentence saying what it measures — on the chart, not in a help article behind a login.
Risk bands, logarithmic regression, dominance, drawdown, ROI by cycle and the technical set — across 14 assets, on daily close.
Retuning a metric silently rewrites every historical chart drawn with it. Each definition carries a version, and a change to the definition changes the version.
We read the rules text of every market on both major venues, score how ambiguously it is written, and record every contract that has already been disputed — always with the clause that raised the flag, never the score on its own.
Disputed volume over time, the contracts contested more than once, and dispute rate by category — from settlement records already held, not estimates.
Five flags: subjective wording, no named source, no edge cases, no timezone, prior dispute. Three of the five fire on what the rules text does not say.
Prediction markets price the macro events that move crypto — rate decisions, inflation prints, recession calls. Those probabilities sit on the same axis as the risk metric, so a forward-looking number and a backward-looking one can be read together.
Illiquid days are left as visible holes rather than interpolated, and the filter that dropped them is stated on the chart. A smooth line drawn through no trading is an invention.
These are risk-neutral prices carrying a risk premium, not forecasts. It says so on the chart, because the difference is the whole thing.
A 2026 study reports that repricing in Kalshi macro contracts forecasts crypto volatility. It was going to be the flagship of this product. We replicated it on our own data, it did not hold — so the feature is not being built, and the study is published instead.
A null we publish is worth more than a feature we cannot defend.
The eight results that survived multiple-testing correction all vanished once a time trend was added: macro repricing rose steadily across the sample while crypto volatility fell, and a regression reads two crossing trends as a relationship. That is in the study too.