The research behind QuantiCRUT™
The suitability screen is not a marketing artifact. Each layer of the methodology — the deduction math, the economic case for simulation, and the paired-path framework itself — rests on published, citable work.
Ten thousand simulated paths. Some favor the trust; many don't. The research below is why the screen can tell which — for a specific client.
Opening the black box
Charitable Remainder Unitrusts (CRUTs) are a mainstay of charitable planning, yet the derivation of the income tax charitable deduction is often treated as a black box. Practitioners routinely rely on IRS actuarial tables without a clear account of the computational steps that produce the published remainder factors. This Article explains the mathematics underlying I.R.C. § 7520 and Treas. Reg. § 1.664-4, translating the operative provisions into explicit formulas. The result is a replicable method for independently verifying remainder factors and constructing proprietary valuation models, illustrated through a companion CRUT calculator implementing the described approach.
Why the answer has to be simulated
Prior studies conclude that charitable remainder trusts (CRTs) make no economic sense for donors without charitable intent, resting on three faulty assumptions: constant investment returns, minimal capital gain realization within the trust, and IRS mortality tables that understate the life expectancy of typical CRT donors. Using Monte Carlo simulation incorporating investment risk, longevity risk, annuitant mortality tables, realistic portfolio turnover, and post-2013 tax rates, this article analyzes funding a retirement portfolio with CRT distributions. Results show a CRT-funded portfolio often produces greater expected retirement income, higher success rates, and a larger bequest than direct funding — even absent charitable motivation.
When does a CRUT outperform?
Earlier Monte Carlo work compared average present values of separately simulated outcomes against a single immediate-liquidation benchmark. This framework advances that approach in three ways. First, it reports a paired-path win probability — CRUT and benchmark run on identical return paths, so the metric captures how often, not merely whether on average, the trust prevails. Second, it evaluates three economically distinct counterfactuals (Hold-and-Draw, Hold-to-Death, Liquidate-and-Reinvest), showing benchmark selection itself often decides suitability. Third, variance-based Sobol sensitivity analysis exposes the basis–longevity interaction that scenario-based designs cannot isolate, yielding a multivariate screening protocol rather than single-parameter guidance.
Behind the Research: an interview with the author — Journal of Financial Planning video series.
Run the screen
The screen puts this research to work on your client's facts: their basis, their ages, their real counterfactual. It informs your judgment. It does not replace it.