back to the survey
finance · station 01

riskmetric

A risk model for Bitcoin DCA — band and cycle risk, shipped as a live dashboard.

survey position
N 52.37° ·E 04.90°
elevation
2,418 m
field status
shipped
role
Builder
stack
Python · Vercel · GitHub Actions
year
2025
links
context

The question is plain: at today’s price, how much risk is a dollar-cost-average buyer actually taking on Bitcoin? The honest answer lives in public data — price history, cycle structure — but it isn’t read off a chart at a glance.

riskmetric reconstructs that read from first principles, so the signal is reproducible rather than asserted.

approach

A power-law fair-value regression sets the spine. Around it, band risk and cycle risk are scored into a single normalised read — calm where the model says calm, elevated where it doesn’t.

A scheduled pipeline refreshes the inputs daily, so the number on screen is never stale and never hand-touched.

daily

the dashboard refreshes itself — no hand on the wheel

result

A live dashboard that updates itself: band and cycle risk, the current read, and the fair-value context behind it.

The logic is legible end to end — every read traces back to the inputs that produced it. It earns trust the way a ledger does.

field capture
The riskmetric dashboard: BTC price against the risk read, with the colour-coded risk metric over the full price history.
the live dashboard — band and cycle risk over the full price history
field readings
cadencedaily, scheduled
surfacelive dashboard
groundpublic price + cycle data
modelpower-law fair value