Equity Compensation Tax Pack

Why this Data Set exists

Most planning tools treat equity comp as an afterthought — a single 'restricted stock value' input on the household summary screen. The reality is that equity comp is a structured, time-varying asset class with grant-by-grant vesting calendars, exercise windows, holding-period requirements, and tax events that can be triggered or deferred. Treating it as a scalar throws away every planning opportunity.

The advisor side is worse. Advisors trying to help equity-rich clients face a documentation problem: the client's grant agreements are PDFs, the vesting schedules are emails, and the exercise history is on a separate platform from the brokerage. Aggregating this into structured data is itself the bottleneck. Without it, advisors give generic advice that frustrates the clients with the highest LTV in their book.

This Data Set provides the structured representation. 150 households spanning early-career RSU recipients through senior executives with NQSO portfolios spanning a decade. Every grant carries a structured grant_type, vesting schedule, vested-to-date calculation, AMT exposure, and exercise-window tracking. The corpus is designed for the platform that wants to give advisors and clients clarity equity-comp deserves.

Use Cases

Who uses this Data Set

What's inside

The 150 households span ten archetypes from F-01 New Grad Tech through P-01 Peak-Earner Corporate Executives, with deliberate weighting toward equity-comp-heavy archetypes. About 40% of the corpus is mid-career tech employees (the modal equity-comp client); 25% are early-career RSU recipients; 20% are senior executives with NQSO and 10b5-1 plans; 10% are founders / early employees with QSBS implications; 5% are real estate investors with employer equity tied to property-management firms.

Every grant in the corpus is structured: grant_type (RSU, ISO, NQSO, ESPP, RSA, restricted RSU), grant date, total share count, strike price (where applicable), vesting schedule (cliff + graded + performance-based), vested-to-date, exercised-to-date, and the in-the-money or underwater status of options. Vesting calendars are explicit month-by-month schedules — your engine doesn't have to interpret 'four-year vest with one-year cliff' from a string description; the actual monthly vest amounts are in the structured data. AMT exposure is pre-computed for each ISO position based on the bargain element at hypothetical exercise. ESPP lookback periods (where the discount applies to the lower of grant-date or purchase-date price) are structured. 83(b) elections are flagged where applicable.

The Data Set ships as JSON, CSV, and Parquet. The WealthSynth Methodology PDF documents the grant-type taxonomy, the vesting-schedule structures, the AMT calculation methodology, and the calibration source for each archetype's typical equity-comp profile (a blend of Carta benchmark data, Glassdoor compensation reports, and SEC filings on executive compensation).

Preview a sample household

A redacted summary of one household from this Data Set — names, employers, exact balances, and metro area are stripped. Ages are bucketed, income and net worth are reported as bands. The full record (and all 150 like it) ships in the ZIP.

Technical Highlights

Sample Schema Fields

{
  "equity_comp.grants[].grant_type": <value>,
  "equity_comp.grants[].vesting_schedule": <value>,
  "equity_comp.grants[].vested_to_date": <value>,
  "equity_comp.amt_exposure": <value>,
  "equity_comp.exercise_windows": <value>
}

Sample queries

households.flatMap(h =>
  h.equity_comp.grants
    .filter(g => g.grant_type === 'ISO' &&
                 g.exercisable_this_year &&
                 g.amt_bargain_element_per_share *
                 g.shares_exercisable >
                 h.taxes.amt_exemption_remaining)
    .map(g => ({ household: h.id, grant: g }))
)

households.flatMap(h =>
  h.equity_comp.grants.flatMap(g =>
    g.vesting_schedule.filter(v =>
      daysBetween(today(), v.vest_date) <= 90 &&
      v.shares * g.current_price >= 50000)
  )
)

households.filter(h =>
  h.demographics.role === 'executive' &&
  h.assets.concentration_pct > 0.25 &&
  !h.equity_comp.has_10b5_1_plan
)

households.map(h => ({
  id: h.id,
  vested_unexercised: h.equity_comp.grants
    .filter(g => ['ISO', 'NQSO'].includes(g.grant_type))
    .reduce((sum, g) => sum +
      Math.max(0, g.current_price - g.strike_price) *
      (g.vested_to_date - g.exercised_to_date), 0)
}))

Methodology

Each household's equity-comp profile is generated against archetype-specific distributions calibrated from public data: Carta benchmark studies (private-company option grants), Glassdoor compensation reports (public-company RSU grants by company tier), and SEC DEF 14A filings (executive compensation). Vesting schedules use realistic structures: 4-year graded with 1-year cliff is dominant for new-hire RSUs; performance-based vesting (PSUs) appears for senior executives. ISO bargain elements and AMT exposure are computed against current spot prices. ESPP lookback discounts use the prevailing 15% lookback structure most companies adopt. 83(b) elections are seeded at a calibrated rate (~30% of early-stage equity recipients elect, ~5% of late-stage). Each grant's vesting calendar is generated month-by-month with realistic acceleration scenarios (single-trigger and double-trigger for executives subject to change-of-control). The corpus passes the WealthSynth consistency validator (vested + unvested + cancelled = total grant; AMT math is internally consistent) and the LLM-as-judge gate. Annual refresh re-runs against current-year tax rates, AMT exemption levels, and ESPP discount-limit rules.

Included Archetypes (10)

Frequently asked questions