市值加權雖是台灣被動投資的主流，卻內建「高點超配、低點殺跌」的結構性缺陷。本研究直接挑戰：在不更動元大台灣卓越 50（0050）與元大台灣中型 100（0051）每季換股邏輯的前提下，單純透過權重最佳化，能否系統性地改善其風險報酬特性？
本研究橫跨 2002 至 2025 年完整市場循環，於兩個獨立股票池上針對純風險導向、訊號驅動與EPO（Enhanced Portfolio Optimization）等九大類策略，執行共 1,142 組參數的系統性網格回測，嚴格採用無向前偏誤的滾動樣本外（Rolling OOS）架構。尤為關鍵的是，因實際 ETF 持有現金與衍生品部位而與全股票假設口徑不一，本研究特意捨棄 ETF 市價，改以「市值加權複製組合」為直接基準，以確保比較一致性並建立嚴格的實證防禦力。
實證結果顯示，在扣除交易成本後，能跨股池穩定擊敗市值加權的策略極其有限。最終，僅有以風險控制為核心的最小變異數策略（MinVar）、融合風險分散的最小變異數與等風險貢獻混合策略（MinVar-ERC Blend, Blend），以及引進外部約束的錨定型強化投資組合最佳化（Anchored EPO，採 MinVar 為錨點）全數勝出。其優勢來源並非追求更高報酬，而是透過將波動率與最大回撤大幅壓縮，換取顯著提升的 Sharpe 與 Sortino 比率。
雙股池對照揭示了單一股池無法洞察的系統性模式：動能訊號的最佳選擇由「股池特性 × 錨點強度」雙維度共同決定。大型股環境一致偏好時序動能（TSMOM）；中型股環境則僅在無錨點或強錨點變體中改採橫截面動能（XSMOM），弱錨點與中性錨點變體仍偏好時序動能。本研究為 Anchored EPO 框架於台灣市場的首次完整實證，並識別出跨股池穩健勝出的配置模型，為台灣被動投資策略進化提供了堅實的量化依據。

While market-cap weighting dominates Taiwan's passive investments, it systematically over-allocates to overvalued assets. This study evaluates whether weight optimization can upgrade the risk-adjusted profiles of Taiwan's large-cap (0050) and mid-cap (0051) equity universes. Using a look-ahead-bias-free rolling out-of-sample framework (2002–2025) across 1,142 configurations, we systematically scan nine strategy classes. To eliminate discrepancies caused by actual ETFs' non-equity holdings, we strictly benchmark all strategies against a market-cap replication portfolio rather than ETF market prices.
The empirical verdict is stringent: after incorporating transaction costs, only three risk-focused strategies consistently outperform across both universes: pure Minimum Variance (MinVar), the MinVar-Equal Risk Contribution hybrid (Blend), and Anchored Enhanced Portfolio Optimization (EPO) with a MinVar anchor. Their advantage stems not from chasing absolute returns, but from drastically reducing volatility and maximum drawdowns, yielding superior Sharpe and Sortino ratios.
Furthermore, cross-universe comparison decodes that the optimal momentum signal is jointly dictated by "universe characteristics × anchor intensity". Large-caps uniformly favor time-series momentum (TSMOM), whereas mid-caps shift toward cross-sectional momentum (XSMOM) only under no-anchor or strong-anchor configurations. As Taiwan's first comprehensive empirical implementation of the Anchored EPO framework, this study uncovers a robust cross-universe configuration for passive strategy optimization.

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