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Vivic Corp (VIVC) Fair Value & Analysis

Consumer Cyclical · US · Market cap $746K

Price$0.0280
Fair Value$0.0301
Upside+7.4%
Quality89/100
Evidence: Medium Range $0.0258 – $0.0438

Fair value as of: Jun 26, 2026

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Analysis

Vivic Corp (VIVC) currently trades at $0.0280, while our model-based Fair Value estimate is $0.0301 — implying the stock looks roughly 7.4% undervalued today. We read business quality at 89/100 (high quality), in the Consumer Cyclical sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: medium) — always confirm before acting.

About the company

Vivic Corp. engages in the distribution of yachts under the Monte Fino and VIVIC brands in internationally. It also provides marine tourism, development of electric powered yachts, operation of yacht marinas, and yacht rental services. The company was incorporated in 2017 and is headquartered in Las Vegas, Nevada.

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Frequently asked questions

Is Vivic Corp (VIVC) undervalued?
As of Jun 26, 2026, our model estimates a fair value of $0.0301 versus a price of $0.0280 — about +7% (undervalued). Model-based estimate, not financial advice.
What is the fair value of VIVC?
Our 21-model fair value for Vivic Corp is $0.0301 (as of Jun 26, 2026), built from audited fundamentals. The current price is $0.0280.
What is the quality score of VIVC?
Vivic Corp has a Quality Score of 89/100, measuring profitability, growth and balance-sheet strength from non-valuation factors.

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.