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Hailun Piano Co (300329) Fair Value & Analysis

Consumer Cyclical · CN · Market cap 3.1B CNY

Price¥11.60
Fair Value¥9.93
Upside-14.4%
Quality95/100
Evidence: Low Range ¥7.45 – ¥12.41

Fair value as of: Jun 24, 2026

Analysis

Hailun Piano Co (300329) currently trades at ¥11.60, while our model-based Fair Value estimate is ¥9.93 — implying the stock looks roughly 14.4% overvalued today. We read business quality at 95/100 (high quality), in the Consumer Cyclical 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

Hailun Piano Co.,Ltd., together with its subsidiaries, engages in the research, development, manufacture, sale, and service of pianos in China and internationally. It also provides art education services. Hailun Piano Co.,Ltd. was incorporated in 2001 and is based in Ningbo City, China.

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Frequently asked questions

Is Hailun Piano Co (300329) undervalued?
As of Jun 24, 2026, our model estimates a fair value of ¥9.93 versus a price of ¥11.60 — about −14% (overvalued). Model-based estimate, not financial advice.
What is the fair value of 300329?
Our 21-model fair value for Hailun Piano Co is ¥9.93 (as of Jun 24, 2026), built from audited fundamentals. The current price is ¥11.60.
What is the quality score of 300329?
Hailun Piano Co 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.