BGI Genomics Co (300676) Fair Value & Analysis
Healthcare · CN · Market cap 14.2B CNY
Analysis
BGI Genomics Co (300676) currently trades at ¥36.58, while our model-based Fair Value estimate is ¥20.06 — implying the stock looks roughly 45.2% overvalued today. We read business quality at 94/100 (high quality), in the Healthcare 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
BGI Genomics Co., Ltd. engages in the provision of research services, comprehensive precision medicine testing solutions, and health management services in China and internationally. The company offers DNA sequencing services comprising plant/animal/microbial whole genome re-sequencing and de novo sequencing; human whole genome sequencing, long-read human whole genome resequencing, and whole exome sequencing; epigenetics whole genome bisulfite sequencing and ChIp-Seq; and metagenomics and 16S/18S/ITS sequencing. It also provides RNA sequencing, long non-coding RNA sequencing, small RNA sequencing, iso-seq / pacbio transcriptome sequencing; single cell sequencing and high throughput single cell RNA-Seq; spatial transcriptome-stereo-seq; immune repertoire and pre-made library sequencing; and bioinformatics solutions. In addition, the company offers mass spectrometry, including proteomics, metabolomics, and multi-omics. Further, it provides clinical solutions for reproductive health, o…
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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.