本篇論文以2018年4月回溯三年共3,493檔台灣核准銷售之境外基金為研究對象，探討主動式管理策略與基金績效之相關性。本研究以標準差、β 係數、Sharpe 指數與總費用率等變數，對基金績效進行迴歸分析，藉以找出預判未來收益的多因子模型。實證結果發現，若以短中長期普遍性適用的投資計劃來看，對未來基金報酬率影響最值得參考的三個變數為：標準差、β 係數及Sharpe值，其中又以 β 係數的影響最為重大。此外，本文亦將基金依照不同期間分為六個區間別，研究結果發現不同期間存在顯著變數的差異，若要精準預測未來績效，此模型不可單獨運用，必須結合其他衡量指標。

In this paper, totally 3,493 overseas funds approved by Taiwan for sale were selected as the research object, and the relevance of active management strategies and fund performance was discussed. In this study, the standard deviation, beta coefficient, Sharpe index, and total cost rate variables were used to perform regression analysis of fund performance, in order to find a multi-factor model for predicting future returns. The empirical results show that if we look at investment plans that are universally applicable in the short, medium, and long terms, three variables that are most valuable for future fund returns are: standard deviation, beta coefficients, and Sharpe index. In addition, this paper also divides the fund into six intervals based on different periods. The results of the study found that there are significant differences in different periods. To accurately predict future performance, this model cannot be used alone and must be combined with other variables.

1. 緒論 1
2. 研究架構 4
2.1 風險屬性評量 5
2.2 決定風險屬性與區域產業配置比例 5
2.3 建置基金多因子模型並完成共同基金配置 7
3. 文獻回顧 8
4. 研究方法 10
4.1 資料來源與處理 10
4.2 迴歸分析 11
4.3 標的篩選 12
5. 實證結果與分析 14
5.1 迴歸結果分析 (月) 15
5.2 迴歸結果分析 (季) 15
5.3 迴歸結果分析 (半年) 17
5.4 迴歸結果分析 (一年) 17
5.5 迴歸結果分析 (兩年) 18
5.6 迴歸結果分析 (三年) 18
6. 結論與建議 21
附錄 22
附錄1：國內F銀行之風險屬性評量表 (上) 22
附錄2：國內F銀行之風險屬性評量表 (下) 23
參考文獻 24

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