Using the intrinsic score method to value stocks of listed banks on the Vietnamese stock market
DOI:
https://doi.org/10.22437/ppd.v14i3.56884Keywords:
Intrinsic score method, Stock valuation, Vietnamese banking sectorAbstract
This study develops and applies the Intrinsic Score Method to estimate the intrinsic values of listed bank stocks in the Vietnamese stock market. The proposed framework integrates accounting-based valuation theory with panel data regression, bank fixed-effects information, and Shapley value decomposition to identify key financial factors associated with market valuation and quantify their relative importance. Quarterly data from 27 Vietnamese listed commercial banks from the second quarter of 2022 to the fourth quarter of 2024 are analyzed using a two-way fixed-effects model. The results indicate that five financial variables—net profit after tax (NPAT), book value per share (BVPS), non-performing loan ratio (NPL), credit growth (CG), and the price-to-earnings ratio (PE)—are significantly associated with banks’ price-to-book (P/B) ratios. Shapley decomposition identifies NPAT as the most important observed financial factor, accounting for 77.06% of the explanatory contribution attributable to the observed financial variables, followed by BVPS at 19.08%. Meanwhile, NPL, CG, and PE contribute comparatively less. The method combines the weighted financial factors with bank-specific fixed-effects information to construct composite Intrinsic Scores, which are subsequently used to estimate intrinsic P/B ratios, intrinsic stock values, and model-implied expected returns. The results identify several banks as potentially undervalued relative to the model-based intrinsic benchmarks. The proposed framework provides a transparent and practical valuation methodology that integrates accounting fundamentals, panel data econometrics, and Shapley decomposition, offering an interpretable decision-support tool for investors in emerging markets.
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