Is DXYZ or ECAT more undervalued in 2026?

CirclFi compares Destiny Tech100 Inc. (DXYZ) and ECAT (ECAT) using 13 institutional-grade valuation models. DXYZ has a Quality of Company score of 1.6/10 while ECAT scores 1.8/10.

Which is a better buy — DXYZ or ECAT?

Compare intrinsic values from 13 independent models against current market prices. CirclFi also calculates Value Trap scores. This is not financial advice — conduct your own analysis.

How do DXYZ and ECAT valuations compare?

DXYZ at $54.11 and ECAT at $15.58 are compared across Bayesian DCF, EPV, EROIC Spread, First Chicago, Markov DDM, and 8 additional models.

DXYZ vs ECAT Valuation Comparison 2026 — Intrinsic Value Analysis

DXYZ

Asset Management

Destiny Tech100 Inc.

Quality

1.6

out of 10

Value Trap

—

Price

$54.11

Last close

Models

5/13

Active

ECAT

Asset Management

ECAT

Quality

1.8

out of 10

Value Trap

—

Price

$15.58

Last close

Models

6/13

Active

Model-by-Model Comparison

Model	Type	DXYZ Fair Value	DXYZ Upside	ECAT Fair Value	ECAT Upside
Bayesian DCF	Intrinsic	$14.32	-73.5%	$4.12	-73.5%
First Chicago	Scenario	$64.96	+23.2%	$18.67	+23.1%
Markov DDM	Intrinsic	—	—	$28.67	+84.0%
ML-RIV	Intrinsic	$•••.••	••.•%	$•••.••	••.•%
Sentiment SOTP	Hybrid	$•••.••	••.•%	$•••.••	••.•%
CUCE Ensemble	Ensemble	$•••.••	••.•%	$•••.••	••.•%

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DXYZ vs ECAT — Which Stock Is More Undervalued?

ECAT scores higher with a 1.8/10 quality rating vs DXYZ's 1.6/10. Both stocks are analyzed daily using SEC EDGAR filings across 13 independent models.

Comparing Destiny Tech100 Inc. (DXYZ) and ECAT (ECAT) across 13 institutional-grade valuation models reveals how each company's intrinsic value stacks up against its market price. CirclFi's engine processes SEC EDGAR 10-K and 10-Q filings, FRED macroeconomic data, and GDELT news sentiment to generate independent fair value estimates daily.

DXYZ currently trades at $54.11 with a QOC of 1.6/10, while ECAT trades at $15.58 with a QOC of 1.8/10.

Both companies are analyzed with models spanning intrinsic (Bayesian DCF, EPV), scenario-based (First Chicago), regime-switching (Markov DDM, RCMH-DCF), machine learning (ML-RIV, FTNN Topology), and ensemble methods (CUCE).