Roll Implied Spread
Roll-implied effective spread.
What it measures
Roll's (1984) implied effective spread: 2·√(−cov(Δp_t, Δp_{t−1})). Bid-ask bounce induces negative serial covariance in transaction-price changes; Roll's estimator inverts that to recover the effective spread from trades alone — no quotes needed. Divergence between the Roll spread and the quoted spread tells you what executions actually cost relative to what the book displays.
References: Roll 1984.
Point-in-time, leak-free
Like every QUANT_API feature, price_discovery.roll_spread is computed point-in-time: each value uses only data that had actually arrived at the timestamp you query — live or historical. No restatements, no backfills that quietly rewrite the past, no look-ahead. The value your backtest sees at a given stamp is the value the live API would have returned at that stamp. How we enforce this is documented on the methodology page.
Windows & transforms
The signal is computed over rolling windows; each window can be served raw or through a transform (z-score, percentile rank, delta…). Which windows and transforms you can query depends on your plan — the signal itself supports:
Plan & access
price_discovery.roll_spread unlocks on the Quant plan ($2,500/mo) and every plan above it. Every new account starts with a 14-day free trial of the Signal plan — no card required. The trial covers Signal-plan features, so you can evaluate the API end-to-end before upgrading to Quant.
Example call
Resolve the latest value for BTC (5m window, zscore transform — both available on the Quant plan):
curl -G https://api.quant-api.dev/v1/features/live \
-H "Authorization: Bearer fk_live_<your_key>" \
--data-urlencode "asset=BTC" \
--data-urlencode "features=price_discovery.roll_spread@5m:zscore"Same key works on /v1/features/historical for point-in-time backtesting — see the API docs.