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Ming Shing Group (MSW) Fair Value & Analysis

Industrials · US · Market cap $18.2M

Price$1.33
Fair Value$0.3400
Upside-74.4%
Quality95/100
Evidence: Low Range $0.2600 – $0.4300

Fair value as of: Jun 24, 2026

Analysis

Ming Shing Group (MSW) currently trades at $1.33, while our model-based Fair Value estimate is $0.3400 — implying the stock looks roughly 74.4% overvalued today. We read business quality at 95/100 (high quality), in the Industrials 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: low).

About the company

Ming Shing Group Holdings Limited, through its subsidiaries, engages in wet trades works in Hong Kong. Its works include plastering, tile laying, brick laying, floor screeding, and marble works. The company serves public and private sectors. Ming Shing Group Holdings Limited was incorporated in 2022 and is based in Cheung Sha Wan, Hong Kong.

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Frequently asked questions

Is Ming Shing Group (MSW) undervalued?
As of Jun 24, 2026, our model estimates a fair value of $0.3400 versus a price of $1.33 — about −74% (overvalued). Model-based estimate, not financial advice.
What is the fair value of MSW?
Our 21-model fair value for Ming Shing Group is $0.3400 (as of Jun 24, 2026), built from audited fundamentals. The current price is $1.33.
What is the quality score of MSW?
Ming Shing Group has a Quality Score of 95/100, 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.