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arXiv · 2607.14556

Impact of Expert-Following Strategies in Financial Asset Recommendation

Ryuki Unno·Koshi Watanabe·Keigo Sakurai·Keisuke Maeda·Takahiro Ogawa·Miki Haseyama
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Abstract

Financial institutions hold rich transaction histories, yet delivering recommendations that simultaneously maximize investment returns and ensure preference alignment remains a significant challenge. Existing approaches, namely return-based and preference-based strategies, each optimize a single objective, resulting in a fundamental trade-off between profitability (ROI) and relevance (nDCG). In this paper, we propose the Expert-Following Strategies: a framework that identifies top-performing investors based on their historical ROI and recommends the assets they purchased, scored by ROI-weighted purchase frequency. Our experiments using real-world transaction histories show that our strategy achieves statistically significant improvement over the market-average baseline in both ROI and nDCG simultaneously across all four thresholds.

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Ryuki Unno, Koshi Watanabe, Keigo Sakurai, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama. 2026-07-16. Impact of Expert-Following Strategies in Financial Asset Recommendation. https://arxiv.org/abs/2607.14556

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