Options context before you pay the premium
A good thesis expressed through a bad contract is still a loss. Quantivo turns a directional idea into a ranked set of executable contracts, with the volatility and liquidity context that decides whether the trade is worth taking at all.
What it does
IV rank and percentile
Implied volatility is presented relative to its own history, so you can tell the difference between a cheap option and a merely low-priced one.
Strike selection by delta
Candidate strikes are selected from a target delta and days-to-expiry band rather than a round number that happens to look attractive.
Liquidity gates
Spread width, open interest, and volume thresholds filter out contracts that look good on paper and fill terribly in practice.
Full lifecycle modelling
Roll, assignment, and expiry behaviour are modelled explicitly so backtested option results reflect how the position would actually have been managed.
How it works
Start from a thesis
A directional signal or statement-derived exposure defines the underlying, the direction, and the expected horizon.
Build the candidate set
The chain is filtered to the delta and expiry band consistent with that horizon.
Apply reality filters
Liquidity, spread, and volatility-rank gates remove contracts that cannot be traded at a sensible price.
Rank and size
Survivors are ranked and sized against the portfolio risk budget, with the reasoning attached.
Where this actually stands
Quantivo is being built in the open. This is what is running today and what is being worked on next — no roadmap items dressed up as shipped features.
Shipped today
Nothing yet. This module is still in design, and the site will say so until that changes.
In progress next
- Long-call contract optimizer with ranked executable candidates (QVP-160)
- Backtest reality models covering fills, costs, liquidity, and options lifecycle (QVP-157)
- Options-chain data licensing under the market-data vendor decision (QVP-163)