Binary logistic regression reveals profitability and valuation ratios predict high returns in Taiwan, suggesting profitability's dominance.
This study investigates the financial determinants of high stock returns, defined as quarterly returns exceeding 20%, in the Taiwan equity market. Using binary logistic regression models, we assess the predictive power of valuation ratios (P/E, P/B, and P/S) and profitability (ROE), under both contemporaneous and one-period lagged specifications. The empirical results reveal that ROE is a consistently strong predictor, with odds ratios indicating a 1–3% increase in the likelihood of high returns per unit increase in profitability. The P/B ratio also shows statistically significant and economically meaningful effects in contemporaneous models, but its predictive value weakens in lagged models. In contrast, the P/E and P/S ratios provide little forward-looking information, especially when lagged. Industry classification, as captured by a dummy variable for electronics firms (ELEC), adds explanatory power, with odds ratios suggesting that electronics firms are significantly more likely to deliver high returns. Overall, the findings emphasize the superior predictive value of profitability over valuation ratios in identifying near-term outperformers.
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Lin et al. (2025) studied this question.
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