本研究以日本年金積立金管理運用獨立行政法人（Government Pension Investment Fund，以下簡稱GPIF）所採用之 ESG 指數投資組合為研究對象，探討責任投資框架下 ESG 指數納入退休基金資產配置之績效表現與最佳化策略。研究期間為 2009 年 11 月至 2026 年 3 月，採用月資料進行實證分析。本文依據 GPIF 公布之資產管理規模比例建構固定權重 ESG 投資組合，並以相同權重建構對應母指數投資組合，透過不同報酬與風險指標分析報酬風險特徵。並建構最大夏普比率策略、最小變異數策略與最大年化報酬策略，在遵循GPIF投資準則及對 GPIF 基準權重偏離限制下進行樣本外最佳化分析。
實證結果顯示ESG 指數配置在提升長期累積報酬的同時，並未明顯增加整體波動風險。超額報酬檢定與 CAPM 迴歸結果亦顯示ESG 投資組合在維持近似市場風險暴露下，仍具有統計顯著之正向超額報酬。而ESG 投資效果仍因主題與區域而異，不宜將 ESG 指數視為單一同質資產類別。
在最佳化策略方面，本文採用滾動視窗方法比較最大夏普比率策略、最小變異數策略與最大年化報酬策略。結果顯示，最大夏普比率策略在提升風險調整後績效與控制下行風險方面較具優勢，為本文較推崇之動態配置策略。相較之下，最小變異數策略雖然在報酬提升幅度上較不明顯，但其權重配置較為穩定且換手率較低，對大型退休基金之實務管理仍具參考價值。於整體而言，ESG 指數投資不僅可作為退休基金落實責任投資之工具，亦可在適當配置限制與動態調整機制下提升長期投資組合效率。

This study examines the ESG index portfolio adopted by Japan’s Government Pension Investment Fund (GPIF) and evaluates its performance under a responsible investment framework. By comparing it with the corresponding parent-index portfolio, this study investigates whether ESG index investing improves long-term performance and risk-adjusted returns.The results show that the ESG portfolio achieves higher annualized and cumulative returns with slightly lower volatility. Excess return tests and CAPM regression further indicate statistically significant positive excess returns without materially increasing market risk exposure. However, performance differs across ESG themes and regions, suggesting that ESG indices should not be treated as a homogeneous asset class.
This study further applies rolling-window portfolio optimization strategies, including Maximum Sharpe Ratio, Minimum Variance, and Maximum Return strategies. The results show that the Maximum Sharpe Ratio strategy is more effective in improving risk-adjusted performance and controlling downside risk, making it the preferred dynamic allocation strategy in this study. Although the Minimum Variance strategy provides less improvement in returns, its lower turnover and more stable allocation offer practical value for large pension fund management. Overall, the findings suggest that ESG index investing can enhance sustainability exposure and improve long-term portfolio efficiency when combined with appropriate allocation constraints and dynamic adjustment mechanisms.

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