| 摘要: | 在全球金融市場日益複雜的背景下，投資者對於更精準與穩健的投資策略需求持續提升。傳統市值加權指數因忽略公司財務基本面的差異而逐漸顯現其侷限性，而Smart Beta策略則憑藉對公司財務因子的深入分析，提供了在風險管理與回報優化方面的嶄新可能性。然而，Smart Beta策略在具體應用中，因未全面納入效率性考量，可能導致投資決策的準確性不足。為解決此問題，本研究嘗試將Smart Beta策略與資料包絡分析法(Data Envelop-ment Analysis, DEA)結合，構建一套能兼顧盈利性與成長性、效率與穩健性的綜合投資評估框架。
本研究以台灣電子業上市公司為對象，選取營業毛利率、資產回報率(ROA)、股本回報率(ROE)等指標衡量獲利能力，並以營業毛利成長率、淨值週轉率及總資產報酬成長率等指標反映成長潛力。透過Smart Beta策略篩選出具備潛在投資價值的股票，並進一步應用DEA模型評估其相對效率，最終篩選出表現最佳的投資標的。研究過程中，對財務指標進行標準化處理(Z分數)，以確保數據具備可比性，並結合超效率模型提升效率評估的精準性。
實證分析顯示，結合Smart Beta與DEA策略的投資組合，不僅在短期(1個月)及中期(2個月)持有期間內均獲得顯著的超額回報，還能有效平衡風險與回報，顯示出其在動態市場中的適應能力。
本研究的貢獻在於首次嘗試將Smart Beta策略與DEA效率評估方法相結合，為金融市場中的投資決策提供了一種兼具理論創新與實務價值的綜合性策略框架。未來可進一步探討此策略在其他產業及不同市場條件下的應用效果，為多因子投資與效率分析的融合發展提供參考。
In the increasingly complex global financial market, investors' demand for more precise and stable investment strategies continues to grow. Traditional market capital-ization-weighted indices, which neglect the fundamental financial differences among companies, have gradually revealed their limitations. In contrast, Smart Beta strategies leverage an in-depth analysis of financial factors to provide innovative opportunities for risk management and return optimization. However, the practical application of Smart Beta strategies often fails to fully incorporate efficiency considerations, poten-tially compromising the accuracy of investment decisions. To address this issue, this study integrates Smart Beta strategies with Data Envelopment Analysis (DEA) to con-struct a comprehensive investment evaluation framework that balances profitability, growth potential, efficiency, and stability.
This research focuses on listed companies in Taiwan's electronics industry, se-lecting indicators such as gross profit margin, return on assets (ROA), and return on equity (ROE) to measure profitability, along with gross profit growth rate, net asset turnover rate, and return on total assets growth rate to reflect growth potential. Through the Smart Beta strategy, stocks with potential investment value are selected, followed by the application of the DEA model to evaluate their relative efficiency, ul-timately identifying the best-performing investment targets. During the study, finan-cial indicators are standardized (Z-scores) to ensure data comparability, and the su-per-efficiency model is incorporated to enhance the precision of efficiency evalua-tions.
Empirical analysis reveals that investment portfolios combining Smart Beta and DEA strategies achieve significant excess returns over both short-term (1 month) and medium-term (2 months) holding periods. These portfolios effectively balance risk and return, demonstrating adaptability in dynamic market environments. |
