Black-Scholes Pricing
Options-derivative mathematics quantifies the fair risk price of every asset. When the market deviates significantly, a robust edge appears — not an opinion.
C = SΦ(d₁) − Ke⁻ʳᵗΦ(d₂)“The market’s uncertainty is not the problem. The problem is failing to quantify it.”
Every signal is the result of the same three filters. No exceptions, no discretion, no stories — only probabilities with verifiable origin.
Options-derivative mathematics quantifies the fair risk price of every asset. When the market deviates significantly, a robust edge appears — not an opinion.
C = SΦ(d₁) − Ke⁻ʳᵗΦ(d₂)Tens of thousands of paths simulate possible price trajectories. What remains is a distribution — and within that distribution, the zone where entry and exit make statistical sense.
Sᵗ₊₁ = Sᵗ·e^(μ−½σ²)Δt + σε√ΔtMulti-timeframe cycles condense the distribution into discrete action zones: Long, Short, Wait. Every zone is time-stamped, auditable, and binds action to a defined probability.
σᵗ ∈ {−1, 0, +1}Excerpt of the BUY cohort, February–April 2026. Figures are referenced live from Yahoo Finance; signals were published before the move.
Every signal runs through the same path — automated, documented, repeatable. Your job is discipline. Ours is mathematics.
Tick, options-chain, and macro feeds across 204 assets. Nothing is manually filtered — raw data or nothing.
Black-Scholes delivers the theoretical price, Monte Carlo the possible trajectories. Discrepancies become the basis of a potential edge.
Multi-timeframe cycles (1D / 4H / 1H) converge to a single decision: Long, Short, Wait — each with its associated probability.
The signal is published with a time-stamp, ahead of any move. The exit zone is already defined before you enter.
Lorenscheit Intelligence is restricted to a small circle of investors who value data over narrative.