Decision support for the options trader who wants the math, not just the answer. QuantMint applies institutional-grade models to estimate theoretical pricing, modeled probabilities, and risk — then translates the output into plain English. Every order is placed by you, in your own brokerage account.
New to options? See how a covered call works in 60 seconds →Direct brokerage integration is coming — beta users get started via CSV or OFX export from Schwab, Fidelity, Vanguard, TD, E*Trade, IBKR, Robinhood, Webull, or Tastytrade.
The full quant stack fires against your positions, live chains, and upcoming events. You don't touch a formula — you see the answer.
Ranked ideas, modeled assignment odds, earnings warnings, and roll alerts — tailored to your book. You evaluate each idea and place the trades.
Start with the trade decision and drill into the model only when you want more depth. QuantMint handles the heavy lifting without hiding the inputs, so you stay in control of the trade.
Core pricing, Greeks, and probabilities come from deterministic models, not language-model guesswork. QuantMint surfaces the inputs behind each recommendation so you can see what is driving the trade.
Every screen leads with the decision, then opens the math. Whether you're writing your first covered call or managing an active book, you get the call and the context in the same place.
Portfolio-level delta, gamma, theta, and vega — plus sector concentration and assignment risk — updated live. Second-order Greeks on every position when you want to go deeper.
A live volatility surface tells you which strikes are actually expensive and which just look that way. IV rank, IV percentile, and skew in one view — the same framework market-makers use to price spreads.
Every spread strategy is sized on max loss, not promise. Negative-EV setups are flagged, not hidden. Bad chain data is caught before it reaches your decision. The math says no when the math says no.
The quant engine scores setups against your actual holdings. Then AI reads the math — probability, Greeks, momentum, earnings, taxes — and explains the trade thesis in plain English so you can evaluate it yourself.
Earnings, FOMC, CPI — every scan flags upcoming events that historically widen volatility. A graduated earnings penalty captures modeled IV crush, and forward vol context shows how the market is pricing the risk. The model surfaces the risk; you decide whether to act.
Every roll candidate is scored on modeled expected value — net credit, strike improvement, modeled assignment probability, and short-term vs. long-term tax impact. You see the trade-off; you decide whether to roll.
Live bid/ask updates across your whole portfolio, with row-level isolation so your positions and analysis never mix with anyone else's. Your book is visible only to you.
If you only care what to do next, you can stop here — the platform delivers the decision, ranked and explained. For the analytical trader who wants to see the stack, the full quant engine is one click away.
Dividend-paying stocks need a dividend-aware pricing model, or premium estimates drift. We use the Merton dividend-adjusted BSM and BS-02 closed-form American pricing.
A fitted vol surface lets you see which strikes are priced rich and which are priced flat — the same approach market-makers use to spot mispricing across the smile.
The forward volatility view responds immediately when market regimes change, helping you size your trades appropriately.
Same inputs, same output. Probabilities are seeded and deterministic, so the number you see in the morning is the number you see in the afternoon — until the inputs change.
You can see exactly what happens to your position if price, time, or volatility moves. Dividend yield is propagated through everything.
Assignment risk is more than just delta. Our composite blends price (terminal probability), time (early-exercise), dividend, and event factors into one modeled metric.
Nine complex momentum signals (VWAP, RSI, MACD, etc) resolve down into a single, easy-to-read directional conviction score.
Each candidate roll is scored on modeled net benefit after credit, modeled assignment probability, earnings exposure, and short-term vs. long-term tax impact.
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