The value relevance of earnings and book value at Vietnamese listed enterprises

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Relevant value is important for information users to make business decisions, and stock prices have an essential relationship to the value relevance about enterprises. The paper aims to investigate the earnings and book value influences on the value relevance of 144 Vietnamese listed enterprises. Selected data are non-financial enterprises with a wide range of industries to ensure representativeness on the Vietnamese stock market. The research implements stakeholder and signaling theory to explain the hypotheses of the model related to earnings per share and book value per share. Time series data are analyzed for three years from 2018 to 2020. The quantitative method is applied to test hypotheses. The results determine that the fixed effects model is suitable. The results also show that the earnings per share positively affect the stock price, but book value per share has a negative impact on the stock price. The paper provides some policy suggestions for investors to make reasonable decisions using relevant information about listed enterprises in Vietnam.

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    • Table 1. Descriptive statistics
    • Table 2. Matrix of correlation
    • Table 3. Ordinary Least Squares (OLS) regression results
    • Table 4. Fixed effects model (FEM) regression results
    • Table 5. F-test results
    • Table 6. Regression results by random effects model (REM)
    • Table 7. Hausman test results
    • Table 8. Hypothesis testing results
    • Conceptualization
      Tran Quoc Thinh, Tran Khanh Lam
    • Formal Analysis
      Tran Quoc Thinh, Nguyen Thi Phung, Tran Khanh Lam
    • Project administration
      Tran Quoc Thinh
    • Supervision
      Tran Quoc Thinh
    • Writing – original draft
      Tran Quoc Thinh, Nguyen Thi Phung, Tran Khanh Lam
    • Writing – review & editing
      Tran Quoc Thinh
    • Data curation
      Nguyen Thi Phung, Tran Khanh Lam
    • Investigation
      Nguyen Thi Phung, Tran Khanh Lam
    • Methodology
      Nguyen Thi Phung, Tran Khanh Lam
    • Resources
      Nguyen Thi Phung, Tran Khanh Lam
    • Software
      Nguyen Thi Phung, Tran Khanh Lam
    • Validation
      Nguyen Thi Phung, Tran Khanh Lam
    • Visualization
      Nguyen Thi Phung, Tran Khanh Lam