CG Oncology, Inc (CGON) Fair Value & Analysis
Healthcare · US · Market cap $4.9B
Analysis
CG Oncology, Inc (CGON) currently trades at $65.73, while our model-based Fair Value estimate is $38.40 — implying the stock looks roughly 41.6% overvalued today. We read business quality at 95/100 (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
CG Oncology, Inc., a late-stage clinical biopharmaceutical company, develops and commercializes cretostimogene grenadenorepvec for patients with bladder cancer in the United States. The company's product candidate is cretostimogene, an investigational oncolytic immunotherapy, which is in phase 2 clinical trials of cretostimogene in patients with high-risk NMIBC after BCG failure; a phase 3 clinical trials to evaluate the safety and efficacy of cretostimogene as monotherapy in the treatment of patients who have received adequate BCG therapy with high-risk BCG-unresponsive, CIS-containing NMIBC and BCG-unresponsive Ta, or T1 papillary tumors; phase 3 BOND-003 Cohort C trials as a single agent; phase 3 BOND-003 Cohort P as a single agent in patients with BCG-UR papillary-only NMIBC. It also develops cretostimogene monotherapy for intermediate-risk NMIBC following TURBT, which is in phase 3 PIVOT-006 clinical trials to assess the safety and efficacy of adjuvant cretostimogene; and creto…
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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.