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In this study we identify low‐risk anomalies affiliated with industry in frontier markets, offering valuable insights for fund managers and investors managing an internationally diversified portfolio. Utilising a two‐beta model—incorporating both market and industry betas—we reveal a distinct low‐beta anomaly with a monthly magnitude of 2.13% tied to risk exposure in affiliated industries, which remains robust after controlling for size and value factors. We extend our analysis further to explore intra‐industry anomalies. We identify a low‐beta anomaly within the energy, healthcare, and industrial sectors, and idiosyncratic volatility (IVOL) anomalies in the energy, healthcare, and real estate sectors, showing consistency when controlling for relevant factors. We also incorporate transaction costs into our analysis and provide recommendations to enhance the profitability of these anomalies by reducing portfolio rebalancing frequency and accounting for tax implications.
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Hourani et al. (2026) studied this question.
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