VirTra, Inc (VTSI) Fair Value & Analysis
Technology · US · Market cap $36.2M
Fair value as of: Jun 25, 2026
Analysis
VirTra, Inc (VTSI) currently trades at $3.20, while our model-based Fair Value estimate is $2.31 — implying the stock looks roughly 27.8% overvalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
VirTra, Inc. provides judgmental use of force training simulators, firearms training simulators, and driving simulators for the law enforcement, military, educational, and commercial markets worldwide. The company offers V-300 simulator, wrap-around screen with video capability for simulation training; V-180 simulator for smaller spaces or smaller budgets; V-100 Simulator and V-100 MIL single-screen based simulator systems; V-ST PRO, a realistic single screen firearms shooting and skills training simulator; and Virtual Interactive Coursework Training Academy (V-VICTA), which enables law enforcement agencies to teach, train, test, and sustain departmental training requirements. It also provides Red Dot Optic Training for accuracy and target acquisition; Subscription Training Equipment Partnership (STEP), a program to utilize simulator products, accessories, and interactive coursework; and V-Author, a software, which allows users to create, edit, and train with content specific to age…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.