Investment Layer · Probabilistic Engine

Vicor · Probabilistic Target Model

Monte Carlo across four scenarios for Vicor Corporation (NASDAQ: VICR). Adjust probability weights and driver distributions. 10,000 draws per run. Target-price and 2-year IRR distributions update live. Companion to the Vicor deep dive.

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1. Scenario picker

Four scenarios describe the FY28 outcome. Adjust probability weights below. They constrain to sum to 100%. Defaults are our current confidence read.

Bear

25%

Rubin lost; licensing plateaus; Advanced Products slows to 10% CAGR

Base

40%

Rubin partial win; licensing $80M/yr; Advanced Products 25% CAGR

Bull

25%

Rubin socket win at scale; licensing wave $150M+; approaches $2.5B

Blue-sky

10%

Rubin sole-source; strategic take-out bid; margin hits 70%

Sum: 100% Current price ($/share): Shares out (M): Cash per share ($):

Weighted expected target

$—

Probability-weighted mean, 10K draws

Median target (P50)

$—

50th percentile of MC distribution

2Y IRR from current

—

Weighted-mean IRR to expected target

P of loss

—

P(target < current price)

2. Driver distributions

Per scenario: P10 / P50 / P90 for FY28 revenue and EV/Sales multiple. All editable. Triangular distribution sampled between P10 and P90 with mode at P50. Revenue and multiple correlated ρ=0.6 within scenario.

Scenario	FY28 Revenue ($M)			EV / Sales multiple
Scenario	P10	P50	P90	P10	P50	P90

3. Monte Carlo target-price distribution

Target-price distribution — 10,000 draws

Vertical lines = P5 / P25 / P50 / P75 / P95. Diamond = weighted expected target. Triangle = current price.

—

P25

—

P50

—

P75

—

P95

—

2-year IRR distribution — from current price

Vertical lines = 0%, 15% hurdle, 25% hurdle. IRR = (target/current)^(1/2) − 1.

P(loss)

—

Median IRR

—

P(IRR≥15%)

—

P(IRR≥25%)

—

P95 IRR

—

4. Sensitivity tornado

Change in weighted expected target when each input's P50 is shifted ±20%. Longer bar = higher sensitivity. Only P50s are perturbed; P10/P90 spread and probability weights are held constant.

5. Methodology

Distributional model

Each scenario draws revenue and EV/Sales from a triangular distribution defined by user-supplied P10/P50/P90. Triangular is compact, matches practitioner scenario intuition, and does not require assuming a mean.

Correlation

Revenue and EV/Sales multiple are positively correlated within each scenario (ρ = 0.6). High-growth outcomes typically print higher multiples; independent draws would understate joint tail risk on both sides.

Scenario mixing

For each of 10,000 iterations, a scenario is selected by the current probability weights, then revenue and multiple are drawn from that scenario's correlated joint distribution.

Target price mechanics

Target = (Revenue × EV/Sales) / Shares outstanding + Cash per share. Assumes zero-debt structure (Vicor carries no meaningful debt). Cash-per-share default $7 reflects ~$300M net cash on 44M shares.

2Y IRR calculation

Annualised return over two years: (Target / Current)^(1/2) − 1. This is the CAGR that reaches the sampled target from current price by end-FY28.

Limits and honest caveats

Model does not incorporate: multiple compression from macro rate shifts, dilution from equity issuance, capital returns (buybacks and dividends), or specific milestone-driven binary re-ratings. Treat outputs as scenario-conditioned reference ranges, not point forecasts.